Integrated diagnostic and therapeutic PAP system

ABSTRACT

The present invention relates to an integrated sleep diagnosis and treatment device, and more particularly to an integrated apnea diagnosis and treatment device. The present invention additionally relates to methods of sleep diagnosis and treatment. The sleep disorder treatment system of the present invention can use a diagnosis device to perform various forms of analysis to determine or diagnose a subject&#39;s sleeping disorder or symptoms of a subject&#39;s sleep disorder, and using this analysis or diagnosis can with or in some embodiments without human intervention treat the subject either physically or chemically to improve the sleeping disorder or the symptoms of the sleeping disorder. The diagnostic part of the system can use many different types of sensors and methods for diagnosing the severity of the symptoms of or the sleep disorder itself. The treatment part of the system can use a device to physically or chemically treat the subject&#39;s symptoms or sleep disorder itself.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of application Ser. No. 13/795,792filed Aug. 26, 2013, which issued into U.S. Pat. No. 9,533,144; which isa continuation of application Ser. No. 11/880,046 filed Jul. 19, 2007,which issued into U.S. Pat. No. 8,545,416, which is a continuation inpart of application Ser. No. 11/266,899 filed on Nov. 4, 2005, whichissued into U.S. Pat. No. 8,172,766.

The U.S. Government has a paid-up license in this invention and theright in limited circumstances to require the patent owner to licenseothers on reasonable terms provided for by the terms of grant number2R44HL075983-02 awarded by the National Institutes of Health.

BACKGROUND OF THE INVENTION

Nearly one in seven people in the United States suffer from some type ofchronic sleep disorder, and only 50% of people are estimated to get therecommended seven to eight hours of sleep each night. It is furtherestimated that sleep deprivation and its associated medical and socialcosts (loss of productivity, industrial accidents, etc.) exceed $150billion per year. Excessive sleepiness can deteriorate the quality oflife and is a major cause of morbidity and mortality due to its role inindustrial and transportation accidents. Sleepiness further hasundesirable effects on motor vehicle driving, employment, higher earningand job promotion opportunities, education, recreation, and personallife.

Primary sleep disorders affect approximately 50 million Americans of allages and include narcolepsy, restless legs/periodic leg movement,insomnia, and most commonly, sleep apnea. Sleep apnea is defined as thecessation of breathing during sleep. The three major types of sleepapnea are obstructive sleep apnea (OSA), central sleep apnea (CSA), andcomplex sleep apnea (COMPSA). Of these three, CSA is rare, while OSA isthe most common. CompSA is a relatively new disease state that manifestsitself after therapy is applied. Patients with CompSA are characterizedby the emergence of new CSA events after the application of ContinuousPositive Airway Pressure (CPAP). USA's prevalence in society iscomparable with diabetes, asthma, and the lifetime risk of colon cancer.OSA is grossly under diagnosed; an estimated 80-90% of persons afflictedhave not received a clinical diagnosis. OSA is characterized byrepetitive pauses in breathing during sleep due to the obstructionand/or collapse of the upper airway (throat), usually accompanied by areduction in blood oxygen saturation, and followed by an awakening tobreathe (an apnea event). Respiratory effort continues during theepisodes of OSA. Multiple episodes of apnea may occur in one night,causing sleep disruption. CSA is a neurological condition causingcessation of all respiratory effort during sleep, usually withcorresponding decreases in blood oxygen saturation. In contrast to OSA,where there is respiratory effort from the brain stem but a physicalblockage prevents inhalation of oxygen, in CSA the brainstem centercontrolling breathing shuts down, resulting in no respiratory effort andno breathing. The subject is aroused from sleep by an automaticbreathing reflex. Frequent activation of the reflex results in verylittle sleep for the subject. The neurological mechanism behind CSA isvery different from the physical cause of OSA. Although the effects ofCSA and OSA are highly similar, effective treatment can differ. CompSAcan be thought of as a combination of OSA and CSA. As mentioned before,CompSA is characterized by an emergence of CSA events after CPAPinitiation.

Medications, hygiene, or some physical form of therapy can be used totreat apneas. Treatment of OSA and CSA vary substantially, which makes aproper diagnosis of the correct type of sleep apnea (OSA, CSA or CompSA)critical for an effective treatment. Apnea treatment is provided basedon the type of apnea, and can be adjusted by re-testing the subject atsome later time to determine whether the condition or the symptoms havebeen alleviated. The most common method of treating OSA is continuouspositive airway pressure (CPAP) and positive airway pressure (PAP)devices applied to the subject's airway to force the subject to breathe.When using a simple CPAP device to treat OSA, the air pressure acts as asplint, holding the airway open and reducing or removing theobstruction. The optimal pressure is determined by a sleep technicianduring a single titration night. The sleep technician manually adjuststhe device to deliver a minimum pressure sufficient to force the airwayopen and reduce the number of apneas. Once the optimal pressure isdetermined, the device is programmed to consistently provide thispressure, and the patient is sent home.

Slightly more advanced PAP devices automatically adjust the gas pressurebased on sensors built into the device. The sensors measure gas flow,pressure, or other fluid characteristics in the device or its mask, andadjust the delivered pressure based on various algorithms known in theart. These auto-PAP devices rely on the single, physiological variable(the measured or estimated fluid characteristics) to predict or detectan apnea event.

None of the devices on the market can be used to adjust the air flowdelivered to a subject based on the subject's current physiologicalstate or the subject's current symptoms. Further, none of the currentdevices can use a rich data set to predict or detect apnea and provideappropriate treatment. Still further, none of the current CPAP or PAPtitration methods use a rich set of data over single or multiple nightsto set the optimal pressure and other parameters. Still even further,none of the current devices can be used to automatically adjust atreatment device based on a comprehensive evaluation of the subject'sphysiological signals. Still even further, none of the current titrationdevices can be used in the subject's home.

It is therefore an object of the present invention to adjust thetreatment gas flow or pressure delivered to the subject based on thesubject's current physiological state or symptoms. It is another objectof the present invention to use a rich data set over multiple nights totitrate the CPAP treatment. It is another object of the presentinvention to use a closed-loop or partially closed-loop system toautomatically titrate the CPAP treatment based on the subject'sphysiological signals. It is still another object of the presentinvention to treat a subject's apnea in a predictive manner. It is stillanother object of the present invention to provide a system or method oftreating a subject's apnea using the subject's physiological signals. Itis still another object of the present invention to provide a device andmethod of titration in the subject's home. It is still another object ofthe present invention to provide a device and method of titration in thehospital's acute or sub-acute settings, such as for postoperativemanagement of care.

SUMMARY OF THE INVENTION

The present invention relates to an integrated sleep diagnosis andtreatment device, and more particularly to an integrated apnea diagnosisand treatment device. The present invention additionally relates tomethods of sleep diagnosis and treatment.

There are numerous embodiments of the present invention with a few ofthose listed below. The present invention further relates to a sleepdiagnosis device integrated with a treatment device. The sleep disordertreatment system of the present invention can use a diagnosis device toperform various forms of analysis to determine or diagnose a subject'ssleeping disorder or symptoms of a subject's sleep disorder, and usingthis analysis or diagnosis can with or in some embodiments without humanintervention treat the subject either physically or chemically toimprove the sleeping disorder or the symptoms of the sleeping disorder.The diagnostic part of the system can use many different types ofsensors and methods for diagnosing the severity of the symptoms of orthe sleep disorder itself. The treatment part of the system can use adevice to physically or chemically treat the subject's symptoms or sleepdisorder itself.

The diagnostic part of the system or device can use various sensors formeasuring the subject's respirations, cardiac signals, brain wavesignals, blood gases, EMG, EOG, airway pressure, and the like. Anysensor that can or has been used with a full polysomnogram (PSG) maylikewise be used alone or in combination with other sensors. Sensors formeasuring the subject's brain wave signals include EEG electrodes andthe like. Sensors for measuring the subject's respirations or oxygenlevels include sensors to measure airflow, respiratory effort,oxygenation and ventilation, and the like. Measurement of airflow ispreferably measured using sensors or devices such as a pneumotachometer,strain gauges, thermal sensors, transducers, piezo sensors,magnetometers, pressure sensors, static charge-sensitive beds, and thelike. These sensors or devices, also preferably measure nasal pressure,respiratory inductance plethysmography, thoracic impedance, expiredcarbon dioxide, tracheal sound and the like. Measurement of respiratoryeffort is preferably measured by esophageal pressure, surfacediaphragmatic EMG, inductive plethysmography, and the like. Measurementof oxygenation and ventilation is preferably measured by pulse oximetry,transcutaneous oxygen monitoring, transcutaneous carbon dioxidemonitoring, expired end carbon dioxide monitoring, and the like.

Signals from these sensors are then analyzed to determine the level ofseverity of the symptoms of the subject's sleep disorder and in somecases to diagnose the sleep disorder itself. One particular embodimentof the present invention involves diagnosing the type and level ofseverity of a subject's sleep apnea and with or without humanintervention adjusting an apparatus for providing positive airwaypressure to the subject. The treatment device can be adjusted by eitherby a closed loop control system (automatically) which uses, in part, thedata or signals from the diagnosis device to actuate a physical orchemical treatment system for the subject, or an open loop controlsystem (manually) which can alert a human who then adjusts the treatmentdevice based in part on the data or signals from the diagnosis device.Alternatively, signals from the sensors can be saved on a medium inorder to be retrieved and analyzed at a later date. Media on which datacan be saved include, but are not limited to chart recorders, harddrive, floppy disks, computer networks, optical storage, solid-statememory, magnetic tape, punch cards, etc.

The diagnostic device can be linked to the treatment deviceelectronically. By electronically linking, it is envisioned that thedevices can be linked through a tether, wireless link or somecombination thereof. These wireless links can be RF, IR, RF cellular, RFinternet, and the like. The diagnostic device preferably incorporateselectronics which allow for the wireless transmission of signals fromthe diagnostic device to an intermediary device or to the treatmentdevice itself. The intermediary device may be a cell phone, a modem, awireless router, a router, a PDA, a computer, a processor, combinationsthereof, and the like. The diagnostic device may transmit signals overany known communications systems or combination thereof to a remotelocation or to the treatment device itself as well. The communicationscan include for example cellular systems, copper wire systems, fiberoptic systems, broad band cable systems, the internet, combinationsthereof and the like.

Signals from these sensors can also be transmitted to a remote locationto allow for remote review or processing of signals for diagnostic ortreatment purposes. This allows for attended home titration of thetreatment device or remotely attended hospital in-patient titration ofthe treatment device. The treatment devices can then either be adjustedautomatically or manually from the remote location, or automaticallyadjusted at the location of the subject being titrated. Because thistitration or adjustment system allows for the more robust collection ofdata from the subjects, this system can be better used to titrate thetreatment device or devices, and in particular can be used to betteradjust a PAP or CPAP device. Since traditional PAP or CPAP devices relyon limited sensor input to adjust the treatment device, mainly airflowpressure at some point on the device, this robust data collected duringthe titration with the diagnostic device can be used to teach or trainthe treatment device to correlate the more robust data from thediagnostic device to limited sensor signatures from the PAP or CPAPdevice to allow for more accurate control. One method of teaching ortraining the treatment device would be to teach or train a neuralnetwork on the treatment device. Another method of titrating thetreatment device would be to use a WAVLET algorithm to adjust theprocessor or controller on the treatment device or more preferably toadjust the PAP or CPAP device

The treatment device can be any device known to those skilled in theart. The treatment device can either physically or chemically treat thesubject's sleeping disorder. An example of physically treating thesubject's sleeping disorder would be a device to provide positive airwaypressure to a subject. The treatment device can either be a traditionalPAP or CPAP, or can include various devices for chemical or medicaltreatment of the subject. The subject may also have two or moretreatment devices that are titrated at the same time. For example, thesubject could have a PAP device that is being titrated at the same timeas a functional electrical stimulation (FES) device. The PAP devicepreferably being used to treat the general obstructive apneas and theFES device preferably for treating central apneas. This application alsocovers the treatment device for use with these features as well as thetreatment device for use with additional sensors. Preferably, the newCPAP or PAP with a respiratory effort belt is used to detect respiratoryeffort. Some way of measuring respiratory effort is needed since thediagnosis of central and complex apneas requires some indication of thelack of respiratory effort.

The treatment device could include an O₂ tank or source, a CO₂ tank orsource, a medication or chemical reservoir, combinations thereof, andthe like. The supplemental oxygen can be used to alleviate symptoms andadverse affects of central and complex apneas. Supplemental oxygen mayeven be used on obstructive apneas. Another example of chemicallytreating the subject's sleeping disorder would be to have a medicationreservoir where a drug is delivered to the subject in order to treatsymptoms of the sleeping disorder. Preferably, this medication reservoiris placed inline with the airflow of a PAP or CPAP device to deliver anebulized medication or drug to the subject's lungs. Also preferably,the PAP or CPAP device can be used to deliver CO₂ to trigger a breathingresponse to treat specific central apneas. A treatment device thattreats the underlying problems of a subject's central or complex sleepapneas by administrating appropriate substances could be titrated andused in conjunction with the PAP or CPAP device. For example,beta-blockers could be automatically administered to treat improperheart function, thus preventing central apneas from occurring. Of courseother substances could be administered depending on the underlyingpathology of the central or complex apneas. It is often the case thatcentral apneas are caused by some cardiac or neuromuscular pathology. Afew of the many embodiments of the present invention are as follows.

In one embodiment the invention is a system for adjusting a positiveairway pressure device comprising a data acquisition system comprisingat least one sensor with a signal, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signal or transmitting a processed signal based atleast in part on the signal from the at least one sensor; and a PAPdevice for treating a patient's sleep apnea, the PAP device comprisingan electrical connection for receiving the signal or processed signaltransmitted from the data acquisition system, and a controller formodifying treatment based on central or complex sleep apneas identifiedfrom the signal or processed signal.

In another embodiment the invention is a system for adjusting a positiveairway pressure device comprising a data acquisition system comprising arespiratory effort belt with a signal, at least one electronic componentfor receiving the signal, and at least one electronic component forre-transmitting the signal or transmitting a processed signal based atleast in part on the signal from the at least one sensor; and a PAPdevice for treating a patient's sleep apnea, the PAP device comprisingan electrical connection for receiving the signal or processed signaltransmitted from the data acquisition system, and a controller formodifying treatment based on central or complex sleep apneas identifiedfrom the signal or processed signal.

In yet another embodiment the invention is a system for adjusting apositive airway pressure device comprising a data acquisition systemcomprising at least one sensor with a signal, at least one electroniccomponent for receiving the signal, and at least one electroniccomponent for re-transmitting the signal or transmitting a processedsignal wirelessly based at least in part on the signal from the at leastone sensor; and a PAP device for treating a patient's sleep apnea, thePAP device comprising a wireless receiver for receiving the signal orprocessed signal transmitted from the data acquisition system, and acontroller for modifying treatment based on central or complex sleepapneas identified from the signal or processed signal.

In still another embodiment the invention is a system for adjusting apositive airway pressure device comprising a data acquisition systemcomprising at least two sensors each with a signal, at least oneelectronic component for receiving the sensor signals, and at least oneelectronic component for re-transmitting the signal or transmitting aprocessed signal based at least in part on the signals from the at leasttwo sensors; and a PAP device for treating a patient's sleep apnea, thePAP device comprising an electrical connection for receiving the signalsor processed signal transmitted from the data acquisition system, and acontroller for modifying treatment based on central or complex sleepapneas identified from the signals or processed signal.

In still yet another embodiment the invention is a system for adjustinga positive airway pressure device comprising a data acquisition systemcomprising at least two sensors each with a signal, at least oneelectronic component for receiving the sensor signals, and at least oneelectronic component for re-transmitting the signal or transmitting aprocessed signal based at least in part on the signals from the at leasttwo sensors, the at least two sensors including at least one respiratoryeffort belt; and a PAP device for treating a patient's sleep apnea, thePAP device comprising an electrical connection for receiving the signalsor processed signal transmitted from the data acquisition system, and acontroller for modifying treatment based on central or complex sleepapneas identified from the signals or processed signal.

In an additional embodiment the invention is a system for adjusting apositive airway pressure device comprising a data acquisition systemcomprising at least two sensors each with a signal, at least oneelectronic component for receiving the sensor signals, and at least oneelectronic component for re-transmitting the signal or transmitting aprocessed signal based at least in part on the signals from the at leasttwo sensors, the at least two sensors including a respiratory effortbelt and a pulse oximetry sensor; and a PAP device for treating apatient's sleep apnea, the PAP device comprising an electricalconnection for receiving the signals or processed signal transmittedfrom the data acquisition system, and a controller for modifyingtreatment based on central or complex sleep apneas identified from thesignals or processed signal.

In but another embodiment the invention is a system for adjusting apositive airway pressure device comprising a data acquisition systemcomprising at least three sensors each with a signal, at least oneelectronic component for receiving the sensor signals, and at least oneelectronic component for re-transmitting the signal or transmitting aprocessed signal based at least in part on the signals from the at leastthree sensors, the at least three sensors including a respiratory effortbelt, a pulse oximetry sensor, and an airflow pressure sensor; and a PAPdevice for treating a patient's sleep apnea, the PAP device comprisingan electrical connection for receiving the signals or processed signaltransmitted from the data acquisition system, and a controller formodifying treatment based on central or complex sleep apneas identifiedfrom the signals or processed signal.

In a further embodiment the invention is a titration system including apositive airway pressure device comprising a data acquisition systemcomprising at least one sensor with a signal for application to apatient, at least one electronic component for receiving the signal, andat least one electronic component for re-transmitting the signal ortransmitting a processed signal based at least in part on the signalfrom the at least one sensor; and a PAP device separate from the dataacquisition system for treating the patient's sleep apnea, the PAPdevice comprising an electrical connection for receiving the signal orprocessed signal transmitted from the data acquisition system, and acontroller which can be programmed or titrated to modify a patient'streatment based on diagnostic central or complex sleep apneas identifiedfrom the signal or processed signal wherein the data acquisition systemwith sensor is used for a limited period of time to program or titratethe PAP device.

In a still further embodiment the invention is a titration systemincluding a positive airway pressure device comprising a battery powereddata acquisition system comprising at least one sensor with a signal forapplication to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signal or transmitting a processed signal based atleast in part on the signal from the at least one sensor; and a PAPdevice separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising an electricalconnection for receiving the signal or processed signal transmitted fromthe data acquisition system, and a controller which can be programmed ortitrated to modify a patient's treatment based on diagnostic central orcomplex sleep apneas identified from the signal or processed signalwherein the data acquisition system with sensor is used for a limitedperiod of time to program or titrate the PAP device.

In yet a further embodiment the invention is a titration systemincluding a positive airway pressure device comprising a modular dataacquisition system comprising at least one sensor with a signal forapplication to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signal or transmitting a processed signal based atleast in part on the signal from the at least one sensor; and a PAPdevice separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising a mechanical connectionfor attaching the modular data acquisition system, an electricalconnection for receiving the signal or processed signal transmitted fromthe data acquisition system, and a controller which can be programmed ortitrated to modify a patient's treatment based on diagnostic central orcomplex sleep apneas identified from the signal or processed signalwherein the data acquisition system with sensor is used for a limitedperiod of time to program or titrate the PAP device and after thelimited period of time can be detached from the PAP system.

In another proposed embodiment the invention is a titration systemincluding a positive airway pressure device comprising a dataacquisition system comprising at least one sensor with a signal forapplication to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forwirelessly re-transmitting the signal or transmitting a processed signalbased at least in part on the signal from the at least one sensor; and aPAP device separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising a wireless receiver forreceiving the signal or processed signal transmitted from the dataacquisition system, and a controller which can be programmed or titratedto modify a patient's treatment based on diagnostic central or complexsleep apneas identified from the signal or processed signal wherein thedata acquisition system with sensor is used for a limited period of timeto program or titrate the PAP device.

In yet another proposed embodiment the invention is a titration systemincluding a positive airway pressure device comprising a dataacquisition system comprising at least one sensor with a signal forapplication to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signal or transmitting a processed signal based atleast in part on the signal from the at least one sensor; and a PAPdevice separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising an electricalconnection for receiving the signal or processed signal transmitted fromthe data acquisition system, a source of carbon dioxide for delivery tothe patient, and a controller which can be programmed or titrated tomodify a patient's treatment based on diagnostic central or complexsleep apneas identified from the signal or processed signal wherein thedata acquisition system with sensor is used for a limited period of timeto program or titrate the PAP device.

In still another proposed embodiment the invention is a titration systemincluding a positive airway pressure device comprising a dataacquisition system comprising a respiratory effort belt with a signalfor application to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signal or transmitting a processed signal based atleast in part on the signal from the respiratory effort belt; and a PAPdevice separate from the data acquisition system for treating thepatients's sleep apnea, the PAP device comprising an electricalconnection for receiving the signal or processed signal transmitted fromthe data acquisition system, and a controller which can be programmed ortitrated to modify a patient's treatment based on diagnostic central orcomplex sleep apneas identified from the signal or processed signalwherein the data acquisition system with sensor is used for a limitedperiod of time to program or titrate the PAP device.

In still yet another proposed embodiment the invention is a titrationsystem including a positive airway pressure device comprising a dataacquisition system comprising at least two sensors each with a signalfor application to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signals or transmitting a processed signal based atleast in part on the signals from the at least two sensors; and a PAPdevice separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising an electricalconnection for receiving the signals or processed signal transmittedfrom the data acquisition system, and a controller which can beprogrammed or titrated to modify a patient's treatment based ondiagnostic central or complex sleep apneas identified from the signalsor processed signal wherein the data acquisition system with sensors isused for a limited period of time to program or titrate the PAP device.

In but another proposed embodiment the invention is a titration systemincluding a positive airway pressure device comprising a dataacquisition system comprising at least two sensors each with a signalfor application to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signals or transmitting a processed signal based atleast in part on the signals from the at least two sensors, the at leasttwo sensors including at least one respiratory effort belt; and a PAPdevice separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising an electricalconnection for receiving the signals or processed signal transmittedfrom the data acquisition system, and a controller which can beprogrammed or titrated to modify a patient's treatment based ondiagnostic central or complex sleep apneas identified from the signalsor processed signal wherein the data acquisition system with sensors isused for a limited period of time to program or titrate the PAP device.

In still but another proposed embodiment the invention is a titrationsystem including a positive airway pressure device comprising a dataacquisition system comprising at least two sensors each with a signalfor application to a patient, at least one electronic component forreceiving the signal, and at least one electronic component forre-transmitting the signals or transmitting a processed signal based atleast in part on the signals from the at least two sensors, the at leasttwo sensors including a respiratory effort belt and a pulse oximetrysensor; and a PAP device separate from the data acquisition system fortreating the patient's sleep apnea, the PAP device comprising anelectrical connection for receiving the signals or processed signaltransmitted from the data acquisition system, and a controller which canbe programmed or titrated to modify a patient's treatment based ondiagnostic central or complex sleep apneas identified from the signalsor processed signal wherein the data acquisition system with sensors isused for a limited period of time to program or titrate the PAP device.

In yet still but another proposed embodiment the invention is atitration system including a positive airway pressure device comprisinga data acquisition system comprising at least three sensors each with asignal for application to a patient or to a PAP device, at least oneelectronic component for receiving the signal, and at least oneelectronic component for re-transmitting the signals or transmitting aprocessed signal based at least in part on the signals from the at leastthree sensors, the at least two sensors including a respiratory effortbelt, a pulse oximetry sensor and an airflow pressure sensor; and thePAP device separate from the data acquisition system for treating thepatient's sleep apnea, the PAP device comprising an electricalconnection for receiving the signals or processed signal transmittedfrom the data acquisition system, and a controller which can beprogrammed or titrated to modify a patient's treatment based ondiagnostic central or complex sleep apneas identified from the signalsor processed signal wherein the data acquisition system with sensors isused for a limited period of time to program or titrate the PAP device.

In but another proposed embodiment the invention is a positive airwaypressure device comprising at least one respiratory effort belt with asignal; a PAP device for treating a patient's sleep apnea, the PAPdevice comprising an electrical connection for receiving the signaltransmitted from the at least one respiratory effort belt applied to thepatient, and a processing unit for determining central and complex sleepapneas based on at least the input signal from the respiratory effortbelt, wherein the processing unit of the PAP device modifies treatmentof the patient based on an identified central or complex apnea.

In still another proposed embodiment the invention is a positive airwaypressure device comprising at least one respiratory effort belt with asignal; a PAP device for treating a patient's sleep apnea comprising anair delivery system for a patient, the PAP device comprising anelectrical connection for receiving the signal transmitted from the atleast one respiratory effort belt applied to the patient, and aprocessing unit for determining the type and nature of the patient'ssleep apnea; and a carbon dioxide delivery system for the patientwherein the processing unit of the PAP device modifies treatmentprovided to the patient based on an identified central or complex apnea.

In still another embodiment the invention is a positive airway pressuredevice comprising at least two sensors comprising a respiratory effortbelt for application to a patient and an airflow pressure sensor; a PAPdevice for treating the patient's sleep apnea, the PAP device comprisingan electrical connection for receiving the signals transmitted from theat least two sensors and a processing unit for determining the type andnature of the patient's sleep apnea wherein the processing unit of thePAP device modifies treatment provided to the patient based on anidentified central or complex apnea.

In still another embodiment the invention is a positive airway pressuredevice comprising at least three sensors comprising a respiratory effortbelt for application to a patient, a pulse oximetry sensor forapplication to the patient and an airflow pressure sensor; a PAP devicefor treating the patient's sleep apnea, the PAP device comprising anelectrical connection for receiving the signals transmitted from the atleast three sensors and a processing unit for determining the type andnature of the patient's sleep apnea wherein the processing unit of thePAP device modifies treatment provided to the patient based on anidentified central or complex apnea.

In still another embodiment the invention is a positive airway pressuredevice comprising at least one respiratory effort belt with a signal andat least one electronic component for receiving the signal andwirelessly re-transmitting the signal or transmitting a processed signalbased at least in part on the signal; a PAP device for treating apatient's sleep apnea, the PAP device comprising a receiver forreceiving the signal or processed signal transmitted from the at leastone respiratory effort belt applied to the patient, and a processingunit for determining central and complex sleep apneas based at least inpart on at least the input signal from the respiratory effort belt,wherein the processing unit of the PAP device modifies treatment of thepatient based on an identified central or complex apnea.

In still another embodiment the invention is a titration systemincluding a positive airway pressure device comprising at least onerespiratory effort belt with a signal for application to a patient; acommunication system for transmitting the signal to a remote station,the remote station for viewing or processing the signal to determinewhether the patient has central or complex sleep apnea; and a PAP devicefor treating a patient's sleep apnea, the PAP device comprising anelectrical connection for receiving a signal wherein the communicationsystem is used to titrate or reprogram the PAP device based at least inpart on the signal from the at least one respiratory effort belt appliedto the patient.

In still another embodiment the invention is a titration systemincluding a positive airway pressure device comprising at least onerespiratory effort belt with a signal for application to a patient; acommunication system for transmitting the signal to a remote station,the remote station for viewing or processing the signal to determinewhether the patient has central or complex sleep apnea; a PAP device fortreating a patient's sleep apnea, the PAP device comprising anelectrical connection for receiving a signal; and a second communicationsystem for sending a titration signal to titrate, adjust or reprogramthe PAP device based at least in part on the signal from the at leastone respiratory effort belt applied to the patient.

In yet still another embodiment the invention is a method fordetermining between central apneas and obstructive apneas comprising thesteps of: applying a PAP device comprising a processing unit to apatient; applying a respiratory effort belt, capable of outputting asignal, to the patient; detecting respiratory effort of the patient withthe respiratory effort belt, transmitting the signal from therespiratory effort belt to the processing unit on the PAP device; andanalyzing the signal from said respiratory effort belt with theprocessing unit on the PAP device to identify central and/or complexsleep apneas.

In yet still another embodiment the invention is a method for titratinga PAP device for improving the treatment of central apneas and/orcomplex sleep apneas comprising the steps of: applying a PAP devicecomprising a processing unit to a patient; applying a respiratory effortbelt, capable of outputting a signal, to the patient, the respiratorybelt having an electronic component for receiving the signal or beingconnected to a data acquisition system having an electronic componentfor receiving the signal, the respiratory belt or data acquisitionsystem further being capable of wirelessly transmitting the signal or aprocessed signal based in part on the signal; detecting respiratoryeffort of the patient with the respiratory effort belt; dentifyingcentral and/or complex sleep apneas based at least in part on the signalfrom the respiratory effort belt creating the processed signal;wirelessly transmitting the signal from the respiratory effort beltdevice or processed signal to the PAP device; and titrating the PAPdevice based at least in part on the identified central and/or complexsleep apneas.

In yet still another embodiment the invention is a method for titratinga PAP device for improving the treatment of central apneas and/orcomplex sleep apneas comprising the steps of: applying a PAP devicecomprising a processing unit to a patient; applying a respiratory effortbelt, capable of outputting a signal, to the patient, the respiratorybelt having an electronic component for receiving the signal or beingconnected to a data acquisition system having an electronic componentfor receiving the signal, the respiratory belt or data acquisitionsystem further being capable of wirelessly transmitting the signal or aprocessed signal based in part on the signal; detecting respiratoryeffort of the patient with the respiratory effort belt; identifyingcentral and/or complex sleep apneas based at least in part on the signalfrom the respiratory effort belt creating the processed signal;wirelessly transmitting the signal from the respiratory effort beltdevice or processed signal to a remote location; and manually titratingthe PAP device through at least in part wireless communication from theremote location based at least in part on the identified central and/orcomplex sleep apneas.

In but still another embodiment the invention is a method for titratinga PAP device for improving the treatment of central apneas and/orcomplex sleep apneas comprising the steps of: applying a PAP devicecomprising a processing unit to a patient; applying a respiratory effortbelt, capable of outputting a signal, to the patient, the respiratorybelt having an electronic component for receiving the signal or beingconnected to a data acquisition system having an electronic componentfor receiving the signal, the respiratory belt or data acquisitionsystem further being capable of wirelessly transmitting the signal or aprocessed signal based in part on the signal; detecting respiratoryeffort of the patient with the respiratory effort belt; viewing thepatient using a video sensor with a signal; identifying central and/orcomplex sleep apneas based at least in part on the signal from therespiratory effort belt creating the processed signal; wirelesslytransmitting the signal from the respiratory effort belt device orprocessed signal to a remote location; transmitting the signal from thevideo sensor or a processed signal from the video sensor to the remotelocation; and manually titrating the PAP device through wirelesscommunication from the remote location based at least in part on theidentified central and/or complex sleep apneas.

In but still another embodiment the invention is a method for titratinga PAP device for improving the treatment of central apneas and/orcomplex sleep apneas comprising the steps of: applying a PAP devicecomprising a processing unit to a patient; applying a respiratory effortbelt, capable of outputting a signal, to the patient, the respiratorybelt having an electronic component for receiving the signal or beingconnected to a data acquisition system having an electronic componentfor receiving the signal, the respiratory belt or data acquisitionsystem further being capable of wirelessly transmitting the signal or aprocessed signal based in part on the signal; detecting respiratoryeffort of the patient with the respiratory effort belt; identifyingcentral and/or complex sleep apneas based at least in part on the signalfrom the respiratory effort belt creating the processed signal;wirelessly transmitting at least in part the signal from the respiratoryeffort belt device or processed signal to a remote location; andtitrating the PAP device through at least in part wireless communicationat least in part from the remote location based at least in part on theidentified central and/or complex sleep apneas over a duration of atleast two sessions.

In but still another embodiment the invention is a method for titratinga PAP device for improving the treatment of central apneas and/orcomplex sleep apneas comprising the steps of: applying a PAP devicecomprising a processing unit to a patient; applying a respiratory effortbelt, capable of outputting a signal, to the patient, the respiratorybelt having an electronic component for receiving the signal or beingconnected to a data acquisition system having an electronic componentfor receiving the signal, the respiratory belt or data acquisitionsystem further being capable of wirelessly transmitting the signal or aprocessed signal based in part on the signal; detecting respiratoryeffort of the patient with the respiratory effort belt; identifyingcentral and/or complex sleep apneas based at least in part on the signalfrom the respiratory effort belt creating the processed signal;wirelessly transmitting at least in part the signal from the respiratoryeffort belt device or processed signal to a remote location; andtitrating the PAP device through wireless communication at least in partfrom the remote location based at least in part on the identifiedcentral and/or complex sleep apneas over a duration of at least threenights.

In still another proposed embodiment the invention is a method fortitrating a PAP device for improving the treatment of central apneasand/or complex sleep apneas comprising the steps of: applying a PAPdevice comprising a processing unit to a patient; applying a respiratoryeffort belt, capable of outputting a signal, to the patient, therespiratory belt having an electronic component for receiving the signalor being connected to a data acquisition system having an electroniccomponent for receiving the signal, the respiratory belt or dataacquisition system further being capable of wirelessly transmitting thesignal or a processed signal based in part on the signal; detectingrespiratory effort of the patient with the respiratory effort belt;identifying central and/or complex sleep apneas based at least in parton the signal from the respiratory effort belt creating the processedsignal; wirelessly transmitting at least in part the signal from therespiratory effort belt device or processed signal to a remote location;and titrating the PAP device through wireless communication at least inpart from the remote location based at least in part on the identifiedcentral and/or complex sleep apneas over a duration of at least fournights.

Finally, in still another embodiment, the present invention includes asleeping disorder treatment system comprising a device for diagnosingand creating a quantitative output of a level of severity of a subject'ssleeping disorder or symptoms comprising a pulse oximeter sensor; and adevice for physically or chemically treating a subject's sleepingdisorder or symptoms, which can be adjusted using in part the output ofthe level of severity of the subject's sleeping disorder.

Additional features and advantages of the invention will be set forth inthe detailed description that follows, and in part will be readilyapparent to those skilled in the art from that description or recognizedby practicing the invention as described herein, including the detaileddescription that follows, the claims, as well as the appended drawings.

It is to be understood that both the foregoing general description andthe following detailed description are merely exemplary of theinvention, and are intended to provide an overview or framework forunderstanding the nature and character of the invention as it isclaimed. The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate various embodimentsof the invention and, together with the description, serve to explainthe principles and operation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 Block diagram an embodiment of part of the diagnostic device ofsleeping disorder treatment system of the present invention.

FIG. 2 Block diagram of one embodiment of the signal processing step ofthe present invention.

FIG. 3 Block diagram of one embodiment of the base station used in thepresent invention.

FIG. 4 Block diagram of an embodiment of a base station of part of thediagnostic device of the sleeping disorder treatment system of thepresent invention.

FIG. 5 Block diagram of an embodiment of the programming firmware in thesignal processing module of part of the diagnostic device of thesleeping disorder treatment system of the present invention.

FIG. 6 Block diagram of an embodiment of the programming of theinterrupt service routine in the firmware in the signal processingmodule of part of the diagnostic device of the sleeping disordertreatment system of the present invention.

FIG. 7 Flowchart of one embodiment of the sleep disorder treatmentsystem of the present invention showing analysis of the physiologicalsignals and adjustment of the treatment device.

FIG. 8 Schematic view of one embodiment of the sleep disorder treatmentsystem of the present invention.

FIG. 9 Schematic representation of one embodiment of the presentinvention used with a subject to acquire EEG signals from the subjectand then transmit them to the receiver and attached computer.

FIG. 10 Schematic representation of one embodiment of the presentinvention showing the remote data acquisition method.

FIG. 11 Block diagram of one embodiment of the present invention showingthe motion artifact rejection process.

FIG. 12 Flowchart illustrating one preprocessing function of the presentinvention.

FIG. 13 Analysis tree for Discrete Wavelet Transform (DWT)/StationaryWavelet Transform (SWT) and wavelet packet decomposition.

FIG. 14 Schematic diagram illustrating a three-level Discrete WaveletTransform (DWT) filter bank.

FIG. 15 Illustration of the frequency bands for the analysis trees shownin FIG. 13.

FIG. 16 Schematic diagram of one embodiment of the data acquisitionsystem of the present invention for estimating the physiological statebased on wavelet analysis.

FIG. 17 Schematic diagram illustrating the function of a comparatorunit.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention is related to a device and method of titrating asleep disorder treatment, particularly positive airway pressure (PAP)and continuous positive airway pressure (CPAP) treatment for sleepapneas. The present invention is further related to the devices used inexecuting the method. The present invention includes various embodimentsof a method of titrating a sleep disorder treatment device. Theseembodiments include but are not limited to one or more of the stepsdescribed herein. The present invention further includes variousembodiments of a device used to titrate a sleep disorder treatment,particularly a PAP or CPAP device. The subjects referred to in thepresent invention can be any form of animal. Preferably the subject is amammal, and more preferably a human. Most preferably, the subject is ahuman being treated for a sleep-related breathing disorder with a PAP orCPAP device.

Various embodiments of the present invention include a step of applyingat least one sensor to the subject. The sensors can be applied at anylocation. Preferably, the sensors are applied in a physician's office orplace of business. The physician's place of business includes but is notlimited to an office building, a freestanding sleep center, locationwithin a hospital, mobile vehicle or trailer, leased space, or similarlocation. Just as preferably, the sensors will be mailed to thesubject's home or other sleeping location, and the subject will thenapply them independently. The subject's sleeping location includes butis not limited to the subject's home, apartment, and the like, as wellas a hotel, nursing facility, or other location where an individualcould sleep and where this analysis could be done more controllablyand/or less expensively than in a sleep lab or hospital setting.

Similarly, the sensors can be applied by a variety of individuals,including but not limited to a physician, nurse, sleep technician, orother healthcare professional. Just as preferably, the sensors could beapplied by the subject or the subject's spouse, friend, roommate, orother individual capable of attaching the various sensors. Morepreferably, the sensors could be applied by the subject or the subject'sspouse, friend, roommate, or other individual capable of attaching thevarious sensors with guidance and instruction. Such guidance andinstruction can include static information such as pamphlets, audiorecordings (on cassettes, compact discs, and the like), video recordings(on videocassettes, digital video discs, and the like), websites, andthe like, as well as dynamic information such as direct real-timecommunication via telephone, cell phone, videoconference, and the like.

The sensors that are used with various embodiments of the presentinvention are described herein but can also be any of those known tothose skilled in the art for the applications of this method. Thecollected physiological, kinetic, and environmental signals can beobtained by any method known in the art. Preferably, those sensorsinclude, but are not limited, to wet or dry electrodes, photodetectors,accelerometers, pneumotachometers, strain gauges, thermal sensors, pHsensors, chemical sensors, gas sensors (such as oxygen and carbondioxide sensors), transducers, piezo sensors, magnetometers, pressuresensors, static charge-sensitive beds, microphones, audio recorders,video cameras, and the like. Optionally, the data includes a videochannel. The invention is envisioned to include those sensorssubsequently developed by those skilled in the art to detect these typesof signals. For example, the sensors can be magnetic sensors. Becauseelectro-physiological signals are, in general, electrical currents thatproduce associated magnetic fields, the present invention furtheranticipates methods of sensing those magnetic fields to acquire thesignal. For example, new magnetic sensors could collect brain wavesignals similar to those that can be obtained through a traditionalelectrode applied to the subject's scalp.

Various embodiments of the present invention include a step for applyingsensors to the subject. This step can be performed or accomplished in anumber of ways. In the simplest form, one sensor is applied to thesubject to measure a single channel of physiological or kinetic data. Ina more complex form, two sensors are applied to the subject and oneadditional sensor is contained within the PAP or CPAP device.Preferably, the set of sensors includes one pulse oximeter applied tothe subject's index finger, one thoracic respiratory effort belt appliedaround the subject's chest, and one airflow or air pressure transducercontained within the PAP or CPAP device. In a still more complex form ofthis step, multiple sensors are applied to the subject to collect datasufficient for a full PSG test. If PSG data are to be collected, thepreferred minimal set of sensors includes sensors for two EEG channels,one EOG channel, one chin EMG channel, one airflow channel, one ECGchannel, one thoracic respiratory effort channel, one abdominalrespiratory effort channel, one pulse oximetry channel, and one shin orleg EMG channel. More preferably, the minimal set of PSG sensors isaugmented with at least one additional channel of EOG, one channel ofsnore, one channel of body position (ex., an accelerometer), one channelof video, and optionally one channel of audio.

Electra-physiological signals such as EEG, ECG, EMG, EOG,electroneurogram (ENG), electroretinogram (ERG), and the like can becollected via electrodes placed at one or several relevant locations onthe subject's body. For example when measuring brain wave or EEGsignals, electrodes may be placed at one or several locations on thesubject's scalp. In order to obtain a good electro-physiological signal,it is desirable to have low impedances for the electrodes. Typicalelectrodes placed on the skin may have an impedance in the range of from5 to 10 kΩ. It is in generally desirable to reduce such impedance levelsto below 2 kΩ. A conductive paste or gel may be applied to the electrodeto create a connection with an impedance below 2 kΩ. Alternatively or inconjunction with the conductive gel, a subject's skin may bemechanically abraded, the electrode may be amplified, or a dry electrodemay be used. Dry physiological recording electrodes of the typedescribed in U.S. Pat. No. 7,032,301 are herein incorporated byreference. Dry electrodes are advantageous because they use no gel thatcan dry out, skin abrasion or cleaning is unnecessary, and the electrodecan be applied in a hairy area such as the scalp. Additionally ifelectrodes are used as the sensors, preferably at least two electrodesare used for each channel of data—one signal electrode and one referenceelectrode. Optionally, a single reference electrode may be used for morethan one channel.

When electrodes are used to collect EEG or brain wave signals, commonlocations for the electrodes include frontal (F), parietal (P), mastoidprocess (A), central (C), and occipital (O). Preferably for the presentinvention, when electrodes are used to collect EEG or brain wave data,at least one electrode is placed in the occipital position andreferenced against an electrode placed on the mastoid process (A). Morepreferably, when electrodes are used to collect EEG or brain wave data,electrodes are placed to obtain a second channel of data from thecentral location. If further EEG or brain wave signal channels aredesired, the number of electrodes required will depend on whetherseparate reference electrodes or a single reference electrode is used.

If electrodes are used to collect cardiac signals using an ECG, they maybe placed at specific points on the subject's body. The ECG is used tomeasure the rate and regularity of heartbeats, determine the size andposition of the heart chambers, assess any damage to the heart, anddiagnose sleeping disorders. An ECG is important as a tool to detect thecardiac abnormalities that can be associated with respiratory-relateddisorders.

As the heart undergoes depolarization and repolarization, electricalcurrents spread throughout the body because the body acts as a volumeconductor. The electrical currents generated by the heart are commonlymeasured by an array of twelve electrodes placed on the alms, legs, andchest. Although a full ECG test typically involves twelve electrodes,only two are required for many tests such as a sleep study. Whenelectrodes are used to collect ECG with the present invention,preferably only two electrodes are used. When two electrodes are used tocollect ECG, preferably one is placed on the subject's left-hand ribcageunder the armpit, and the other preferably on the right-hand shouldernear the clavicle bone. Optionally, a full set of twelve ECG electrodesmay be used, such as if the subject is suspected to have a cardiacdisorder. The specific location of each electrode on a subject's body iswell known to those skilled in the art and varies between bothindividuals and types of subjects. If electrodes are used to collectECG, preferably the electrode leads are connected to a component of thedata acquisition system that includes a processing or pre-processingmodule that measures potential differences between selected electrodesto produce ECG tracings.

The two basic types of ECG leads are bipolar and unipolar. Bipolar leads(standard limb leads) have a single positive and a single negativeelectrode between which electrical potentials are measured. Unipolarleads (augmented leads and chest leads) have a single positive recordingelectrode and use a combination of the other electrodes to serve as acomposite negative electrode. Either type of lead is acceptable forcollecting ECG signals in the present invention.

Other sensors can be used to measure various parameters of a subject'srespirations. Measurement of airflow is preferably measured usingsensors or devices such as a pneumotachometer, strain gauges, thermalsensors, transducers, piezo sensors, magnetometers, pressure sensors,static charge-sensitive beds, and the like. These sensors or devicesalso preferably measure nasal pressure, respiratory inductanceplethysmography, thoracic impedance, expired carbon dioxide, trachealsound, snore sound, blood pressure and the like. Measurement ofrespiratory effort is preferably measured by a respirationpiezo-electric sensor, inductive plethysmography esophageal pressure,surface diaphragmatic EMG, and the like. Measurement of oxygenation andventilation is preferably measured by pulse oximetry, transcutaneousoxygen monitoring, transcutaneous carbon dioxide monitoring, expired endcarbon dioxide monitoring, and the like.

Optionally, sensors for directly or indirectly measuring respirationscan be located in the conduit connecting the PAP or CPAP blower to thegas delivery mechanism. These sensors can include airflow sensors, airpressure sensors, or other sensors to measure characteristics of thegas. Further optionally, sensors can be located near the blowermechanism. These blower sensors can estimate or indirectly measureairflow or air pressure by measuring fan speed or power consumption.Methods of determining airflow or air pressure from sensors placed in oron a PAP or CPAP device are generally known in the art, and any suchmethod is appropriate for the present invention.

One example of such a sensor for measuring respirations either directlyor indirectly is a respiration belt. Respiration belts can be used tomeasure a subject's abdominal and/or thoracic expansion over ameasurement time period. The respiration belts may contain a straingauge, piezo-electric, pressure transducer, or other sensors that canindirectly measure a subject's respirations and the variability ofrespirations by providing a signal that correlates to thethoracic/abdominal expansion/contractions of the subject'sthoracic/abdominal cavity. If respiration belts are used, they may beplaced at one or several locations on the subject's torso or in anyother manner known to those skilled in the art. Preferably, when athoracic respiration belt is used, it is positioned below the axilla tomeasure rib cage excursions. When an abdominal respiration belt is used,it is positioned at the level of the umbilicus to measure abdominalexcursions. Optionally, at least two belts are used, with one positionedat the axilla and the other at the umbilicus.

Another example of a sensor or method for measuring respirations eitherdirectly or indirectly is a nasal cannula or a facemask used to measurethe subject's respiratory airflow. Nasal or oral airflow can be measuredquantitatively and directly with a pneumotachograph consisting of apressure transducer connected to either a standard oxygen nasal cannulaplaced in the nose, a facemask over the subject's mouth and nose, or thePAP or CPAP gas delivery mechanism. Airflow can be estimated bymeasuring nasal or oral airway pressure that decreases duringinspiration and increases during expiration. Inspiration and expirationproduce fluctuations on the pressure transducer's signal that isproportional to airflow. A single pressure transducer can be used tomeasure the combined oral and nasal airflow. Alternatively, the oral andnasal components of these measurements can be acquired directly throughthe use of at least two pressure transducers, one transducer for eachcomponent. Optionally, the pressure transducer(s) are internal to thepatient interface box. If two transducers are used for nasal and oralmeasurements, preferably each has a separate air port into the patientinterface box.

When respirations are measured via airflow or air pressure transducers,preferably the sensors are internal to the PAP or CPAP device itself,either in the PAP or CPAP gas delivery mechanism (i.e., the mask orcannula), or positioned near the blower as described above. Transducersin the PAP or CPAP mask or cannula operate identically to the masks andcannulae described above. Optionally, sensors can be located in theconduit connecting the PAP or CPAP blower to the gas delivery mechanism.Methods of determining airflow or air pressure from sensors placed in oron a PAP or CPAP device are generally known in the art, and any suchmethod is appropriate for the present invention.

Sensors placed on a mask or cannula can also be used to determine otherphysiological characteristics. Software filtering can obtain “snoresignals” from a single pressure transducer signal by extracting the highfrequency portion of the transducer signal. This method can eliminatethe need for a separate sensor, such as a microphone or anothertransducer, and also reduces the system resources required to detectboth snore and airflow. A modified nasal cannula or facemask connectedto a carbon dioxide or oxygen sensor may be used to measure respectiveconcentrations of these gases. In addition, a variety of other sensorscan be connected with either a nasal cannula or facemask to measure asubject's respirations directly or indirectly.

Still another example of a sensor or method of directly or indirectlymeasuring respirations of the subject is a pulse oximeter. The pulseoximeter can measure the oxygenation of the subject's blood by producinga source of light at two wavelengths (typically at 650 nm and 905, 910,or 940 nm). Hemoglobin partially absorbs the light by amounts thatdiffer depending on whether it is saturated or desaturated with oxygen.Calculating the absorption at the two wavelengths leads to an estimateof the proportion of oxygenated hemoglobin. Preferably, pulse oximetersare placed on a subject's earlobe or fingertip. More preferably, thepulse oximeter is placed on the subject's index finger. In oneembodiment of the present invention, a pulse oximeter is built-in orhard-wired to the interface box. Alternatively, the pulse oximeter canbe a separate unit in communication with either the interface box or thebase station via either a wired or wireless connection.

Kinetic data can be obtained by accelerometers placed on the subject.Alternatively, several accelerometers can be placed in various locationson the subject, for example on the head, wrists, torso, and legs. Theseaccelerometers can provide both motion and general position/orientationdata by measuring gravity. These accelerometers can be used to detectwhen patients go to sleep or to detect movements during sleep which areimportant factors in assessing the actual sleep time which is animportant parameter used to generate an accurate assessment of nocturnalrespiratory events (such as apnea/hypopnea events, which is the sum ofall apneas and hypopneas divided by sleep time; or apnea/hypopnea index[AHI]). A video signal can also provide some kinetic data afterprocessing. Alternatively, stereo video signals can providethree-dimensional position and motion information. Kinetic data includesbut is not limited to frequent tossing and turning indicative of anunsuitable mattress, excessive movement of bedding indicating unsuitablesleeping temperatures, unusual movement patterns indicating pain, andthe subject's sleeping position.

Other sensors can be used to measure various parameters of a subject'sphysiological, kinetic, or environmental conditions. These otherparameters are preferably measured using sensors or devices such as aphotodetectors, light meters, accelerometers, pneumotachometers, straingauges, thermal sensors, pH sensors, chemical sensors, gas sensors (suchas carbon monoxide detectors), transducers, piezo sensors,magnetometers, pressure sensors, static charge-sensitive beds, audiomonitors, microphones, reflective markers, video monitors, hygrometers,and the like. Because the system is programmable, potentially anytransducer-type sensor that outputs an electrical signal can be usedwith the system.

Various embodiments of the present invention include the step ofconnecting sensors to a data acquisition system. The sensors can beconnected to the data acquisition system either before or after they areapplied to the subject. The sensors can be permanently hardwired to atleast part of the data acquisition system. More preferably, the sensorsare connected to at least part of the data acquisition system via areleasable connector. Optionally, the sensors can be connected to atleast part of the data acquisition system via non-releasable connectorthat does not permit disconnection without destruction of the connector.The physiological sensors are generally hardwired (permanently or via aconnector) to the data acquisition system, but the ongoing evolution inwireless sensor technology may allow sensors to contain transmitters.Optionally, such sensors are wirelessly connected to the dataacquisition system. As such, these sensors and the wireless connectionmethod are considered to be part of the present invention. With theadvances in microelectromechanical systems (MEMS) sensor technology, thesensors may have integrated analog amplification, integrated A/Dconverters, and integrated memory cells for calibration, allowing forsome signal conditioning directly on the sensor before transmission.

Preferably, the sensors are all connected in the same way at the sametime, although this certainly is not required. It is possible, but lesspreferable, to connect the sensors with a combination of methods (i.e.,wired or wireless) at a combination of times (i.e., some beforeapplication to the subject, and some after application to the subject).The sensors can be connected to various parts of the data acquisitionsystem. For example, a thoracic respiratory effort belt can be connectedto a patient interface box while a pulse oximeter can be connected abase station. Further, some sensors may not be attached to the subjectat all. Examples of such sensors include airflow sensors that are partof the PAP or CPAP device and video cameras or microphones that areplaced in the subject's sleeping area. Although these sensors are notattached to the subject, they are still connected to at least onecomponent of the data acquisition system.

Various embodiments of the present invention use a data acquisitionsystem capable of both (a) receiving signals from the sensors applied toor placed near the subject; and (b) retransmitting the signals ortransmitting another signal based at least in part on at least one ofthe collected signals. In its simplest form, the data acquisition systempreferably should interface with the sensors and retransmit the signalsfrom the sensors. Preferably, the data acquisition system wirelesslytransmits the signals from the sensors. Optionally, the data acquisitionsystem also pre-processes the signals from the sensors and transmits thepre-processed signals. Further optionally, the data acquisition is alsocapable of storing the signals from the sensors and/or any pre-processedsignals.

Optionally, the data acquisition system can be a single box, such as apatient interface box, containing a sensor interface module, apre-processor module, and a transmitter module. Further optionally, thedata acquisition system could consist of several boxes that communicatewith each other, each box containing one or more modules. For example,the data acquisition system could consist of: (a) a patient interfacebox containing a sensor interface module, a pre-processor, atransmitter, and a receiver; and (b) a base station box containing asecond pre-processor, a transmitter, and a receiver. In this example,the transmitter and receiver of the patient interface box are used tocommunicate with the base station box. The transmitter and receiver ofthe base station box are used to both communicate with the patientinterface box and a remote monitoring station, remote analysis station,remote data storage station, and the like. Similarly, the dataacquisition could consist of (a) a patient interface box containing asensor interface module, a transmitter, and a receiver; (b) a processorbox containing a pre-processor, a transmitter, and a receiver; and (c) abase station box containing only a receiver and a transmitter. In theseconfigurations, it is not necessary for the transmitters to be of thesame type. For example, the transmitter in the patient interface box canbe a wired, Bluetooth, or other transmitter designed for shortdistances, and the transmitter in the base station box can be a WiFi,IEEE 802.11, TCP/IP, or other transmitter designed to establishconnections over larger distances.

Several data acquisition systems are suitable for use with the presentinvention. Preferably, the data acquisition system is a device fromCleveland Medical Devices, Inc. (CleveMed). All current suitableCleveMed data acquisition systems include a patient interface box and abase station. The three CleveMed patient interface boxes described belowallow for data backup and storage on a removable SD memory card, with asingle 1 GB card providing over 60 hours of recording. The currentCleveMed data acquisition systems also each include a base stationweighing 130 g that is powered by USB. The USB cable also provides awired link between the base station and a PC. The CleveMed patientinterfaces and base stations contain integrated wireless technology forreal-time data transmission within 100 feet line of sight. The CleveMedpatient interface boxes currently suitable for use with the presentinvention include the SleepScout™, Crystal Monitor® 20, and Sapphire™PSG systems.

The SleepScout™ is a wireless patient interface box that includes atotal of 9 input channels for ECG, EMG, thoracic and abdominalrespiratory efforts, snore and a generic auxiliary DC input. Two of thechannels are fully-programmable, adding flexibility by allowing for anycombination of EEG, ECG, EOG or EMG. SleepScout™ also includes severalbuilt-in sensors, including body position, pulse oximetry,pressure-based airflow, and a differential pressure transducer thatallows for PAP or CPAP titration studies. The SleepScout™ patientinterface box weighs 190 g and is powered by two AA lithium batteries.The SleepScout™ transmits data in the 2.4-2.484 GHz ISM band.

The CleveMed Sapphire™ is a wireless patient interface box that includesa total of 22 input channels, including 6 EEG, 2 EOG, 5 EMG, as well asECG, temperature, body position, and respiratory effort. Six of thechannels are EEG, allowing the Sapphire™ to meet guidelines forconducting polysomnogram tests. The Sapphire™ also includes severalbuilt-in sensors, including body position, pulse oximetry, and a genericauxiliary DC input. The Sapphire™ patient interface box weighs 538 g andis powered by two AA lithium batteries. The Sapphire™ transmits data inmultiple bands, allowing dynamic selection of Wireless Medical TelemetryService (WTMS) bands (608-614 MHz, 1427-1432 MHz) and two ISM bands(902-928 MHz or 2.4-2.485 GHz), depending on the availability andsaturation of transmission bands in the testing location.

The CleveMed Crystal® Monitor 20 is a family of wireless patientinterface boxes. Each Crystal® Monitor 20 includes a total of 14 inputchannels, including two each for EEG, EOG, and EMG, as well as ECG andthoracic and abdominal respiratory efforts. The Crystal® Monitor 20 alsoincludes several built-in sensors, including body position, pulseoximetry, pressure-based airflow, and a generic auxiliary DC input. TheCrystal® Monitor 20 patient interface box weighs 210 g and is powered bytwo AA lithium batteries. The Crystal® Monitor 20 family transmits datain multiple bands; the Crystal® 20-S transmits in the 900 MHz ISM band,and the Crystal® 20-B transmits in the 2.4 GHz ISM band. Selection ofthe appropriate Crystal® Monitor depends upon the availability andsaturation of transmission bands in the testing location.

The data acquisition system is preferably portable. By portable, it ismeant, among other things, that the device is capable of beingtransported relatively easily. Relative ease in transport means that thedevice is easily worn and carried, generally in a carrying case, to thepoint of use or application and then worn by the subject withoutsignificantly affecting any range of motion. Furthermore, any componentsof the data acquisition system that are attached to or worn by thesubject, such as the sensors and patient interface box, should also belightweight. Preferably, these subject-contacting components of thedevice (including the sensors and the patient interface box) weigh lessthan about 10 lbs., more preferably less than about 7.5 lbs., even morepreferably less than about 5 lbs., and most preferably less than about2.5 lbs. The subject-contacting components of the device preferably arebattery-powered and use a data storage memory card and/or wirelesstransmission of data, allowing the subject to be untethered.Furthermore, the entire data acquisition system (including thesubject-contacting components as well as any other sensors, a basestation, or other components) preferably should be relativelylightweight. By relatively lightweight, it is meant preferably theentire data acquisition system, including all components such as anyprocessors, computers, video screens, cameras, and the like preferablyweigh less in total than about 20 lbs., more preferably less than about15 lbs., and most preferably less than about 10 lbs. This dataacquisition system preferably can fit in a reasonably sized carryingcase so the subject or assistant can easily transport the system. Bybeing lightweight and compact, the device should gain greater acceptancefor use by the subject.

Various embodiments of the present invention use a data acquisitionsystem capable of storing and/or retransmitting the signals from thesensors or storing and/or transmitting another signal based at least inpart on at least one of the signals. The data acquisition system can beprogrammed to send all signal data to the removable memory, to transmitall data, or to both transmit all data and send a copy of the data tothe removable memory. When the data acquisition system is programmed tostore a signal or pre-processed signal, the signals from the sensors canbe saved on a medium in order to be retrieved and analyzed at a laterdate. Media on which data can be saved include, but are not limited tochart recorders, hard drive, floppy disks, computer networks, opticalstorage, solid-state memory, magnetic tape, punch cards, etc.Preferably, data are stored on removable memory. For both storing andtransmitting or retransmitting data, flexible use of removable memorycan either buffer signal data or store the data for later transmission.Preferably, nonvolatile removable memory can be used to customize thesystem's buffering capacity and completely store the data.

If the data acquisition system is configured to transmit the data, theremovable memory acts as a buffer. In this situation, if the dataacquisition system loses its connection with the receiving station, thedata acquisition system will temporarily store the data in the removablememory until the connection is restored and data transmission canresume. If, however, the data acquisition system is configured to sendall data to the removable memory for storage, then the system does nottransmit any information at that time. In this situation, the datastored on the removable memory can be retrieved by either transmissionfrom the data acquisition system, or by removing the memory for directreading.

The method of directly reading will depend on the format of theremovable memory. Preferably the removable memory is easily removableand can be removed instantly or almost instantly without tools. Thememory is preferably in the form of a card and most preferably in theform of a small easily removable card with an imprint (or upper or lowersurface) area of less than about two in². If the removable memory isbeing used for data storage, preferably it can write data as fast as itis produced by the system, and it possesses enough memory capacity forthe duration of the test. These demands will obviously depend on thetype of test being conducted, tests requiring more sensors, highersampling rates, and longer duration of testing will require faster writespeeds and larger data capacity. The type of removable memory used canbe almost any type that meets the needs of the test being applied. Someexamples of the possible types of memory that could be used include butare not limited to Flash Memory such as CompactFlash, SmartMedia,Miniature Card, SD/MMC, Memory Stick, or xD-Picture Card. Alternatively,a portable hard drive, CD-RW burner, DVD-RW burner or other data storageperipheral could be used. Preferably, a SD/MMC—flash memory card is useddue to its small size. A PCMCIA card is least preferable because of thesize and weight.

When the data acquisition system is programmed to retransmit the signalsfrom the sensors, preferably the data acquisition system transmits thesignals to a processor for analysis. More preferably, the dataacquisition system immediately retransmits the signals to a processorfor analysis. Optionally, the data acquisition system receives thesignals from one or more of the aforementioned sensors and stores thesignals for later transmission and analysis. Optionally, the dataacquisition system both stores the signals and immediately retransmitsthe signals.

When the data acquisition system is programmed to retransmit the signalsfrom the sensors or transmit a signal based at least in part on thesignal from the sensors (collectively “to transmit” in this section),the data acquisition system can transmit through either a wirelesssystem, a tethered system, or some combination thereof. When the systemis configured to transmit data, preferably the data transmission steputilizes a two-way (bi-directional) data transmission. Using two-waydata transmission significantly increases data integrity. Bytransmitting redundant information, the receiver (the processor,monitoring station, or the like) can recognize errors and request arenewed transmission of the data. In the presence of excessivetransmission problems, such as transmission over excessive distances orobstacles absorbing the signals, the data acquisition system can controlthe data transmission or independently manipulate the data. With controlof data transmission it is also possible to control or re-set theparameters of the system, e.g., changing the transmission channel orencryption scheme. For example, if the signal transmitted issuperimposed by other sources of interference, the receiving componentcould secure a flawless transmission by changing the channel. Anotherexample would be if the transmitted signal is too weak, the receivingcomponent could transmit a command to increase the transmitting power.Still another example would be for the receiving component to change thedata format of the transmission, e.g., in order to increase theredundant information in the data flow. Increased redundancy allowseasier detection and correction of transmission errors. In this way,safe data transmissions are possible even with the poorest transmissionqualities. This technique opens a simple way to reduce the transmissionpower requirements, thereby reducing the energy requirements andproviding longer battery life. Another advantage of a bi-directionaldigital data transmission lies in the possibility of transmitting testcodes in order to filter out external interferences, for example,refraction or scatter from the transmission current. In this way, it ispossible to reconstruct falsely transmitted data.

Data compression using lossless encoding techniques can provide basicthroughput optimization, while certain lossy encoding techniques willoffer far greater throughput while still providing useful data. Lossyencoding techniques may include but are not limited to decimation, ortransmission of a compressed image of the data. The preferred method forencoding will include special processing from the transmitter that willpreprocess the data according to user-selectable options, such asdigital filtering, and take into the account the desired visualrepresentation of that information, such as pixel height and targetimage width. Facilities can be made within the system to control theencoding in order to optimize utilization on any given network. Controlover—the encoding methods may include, but is not limited to selectionof a subset of the entire set of signals, target image size, anddecimation ratio.

Data encryption can be applied to secure data transmissions over anynetwork. Encryption methods may include but are not limited to simpleobfuscation and sophisticated ciphers. The preferred embodiment ofsecure data transmission that is compatible with HIPAA and HCFAguidelines will be implemented using a virtual private network. Morepreferably, the virtual private network will be implemented using aspecialized security appliance, such as the PIX 506E, from CiscoSystems, Inc, capable of implementing IKE and IPSec VPN standards usingdata encryption techniques such as 168-bit 3DES, 256-bit AES, and thelike. Still more preferably, secure transmission will be provided by athird party service provider or by the healthcare facility's informationtechnology department. The system will offer configuration managementfacilities to allow it to adapt to changing guidelines for protectingpatient health information (PHI).

Several preferable embodiments of this method employ a wireless dataacquisition system. This wireless data acquisition system consists ofseveral components, each wirelessly connected. Data is collected fromthe sensors described above by a patient interface box. The patientinterface box then wirelessly transmits the data to a separate signalpre-processing module, which then wirelessly transmits the pre-processedsignal to a receiver. Alternatively, the patient interface box processesthe signal and then directly transmits the processed signal directly tothe receiver using wireless technology. Further alternatively, thepatient interface box wirelessly transmits the signals to the receiver,which then pre-processes the signal. Preferably, the wireless technologyused by the data acquisition system components is radio frequency based.Most preferably, the wireless technology is digital radio frequencybased. The signals from the sensors and/or the pre-processed signals aretransmitted wirelessly to a receiver, which can be a base station, atransceiver hooked to a computer, a personal digital assistant (PDA), acellular phone, a wireless network, or the like. Most preferably, thephysiological signals are transmitted wirelessly in digital format to areceiver.

Wireless signals between the wireless data acquisition system componentsare both received and transmitted via frequencies preferably less thanabout 2.0 GHz. More preferably, the frequencies are primarily 902-928MHz, but Wireless Medical. Telemetry Bands (WMTS), 608-614 MHz,1395-1400 MHz, or 1429-1432 MHz can also be used. The present inventionmay also use other less preferable frequencies above 2.0 GHz for datatransmission, including but not limited to such standards as Bluetooth,WiFi, IEEE 802.11, and the like.

When a component of the wireless data acquisition system is configuredto wirelessly transmit data, it is preferably capable of conducting a RFsweep to detect an occupied frequency or possible interference. Thesystem is capable of operating in either “manual” or “automatic” mode.In the manual mode, the system conducts an RF sweep and displays theresults of the scan to the system monitor. The user of the system canthen manually choose which frequency or channel to use for datatransmission. In automatic mode, the system conducts a RF sweep andautomatically chooses which frequencies to use for data transmission.The system also preferably employs a form of frequency hopping to avoidinterference and improve security. The system scans the RF environmentthen picks a channel over which to transmit based on the amount ofinterference occurring in the frequency range.

In this application, transmitting the data wirelessly means that thedata is transmitted wirelessly at least in part of the data transferprocess. This means, for example, that the data may be transmittedwirelessly from the patient interface box to the base station, whichthen transmits the data via either a wireless method, such as a wirelesscellular card, local wireless network, satellite communication system,and the like, or a wired method, such as a wired internet connection,the testing facility's LAN, and the like. Transmitting the datawirelessly also means, for example, that the data may be transmitted viawired connection from the patient interface box to a base station, whichthen wirelessly transmits the data wirelessly via any wireless method,such as Bluetooth, IEEE 802.11, wireless cellular card, satellitecommunication system, and the like to a database that distributes thedata over a hardwired system to a sleep unit or lab. Transmitting thedata wirelessly also means, for example, that the data may be wirelesslytransmitted directly from the patient interface box via WiFi or IEEE802.11, Bluetooth, wireless cellular card, and the like to a processor,which then transmits the processed data to the sleep unit or laboratory.Preferably, the patient interface box wirelessly transmits the data.This allows for a simplified subject hookup and improved subjectmobility.

Preferably, the data acquisition system retransmits the signals from thesensors applied to the subject or transmits a signal based at least inpart on at least one of the physiological, kinetic, or environmentalsignals at substantially a same time as the signal is received orgenerated. At substantially the same time preferably means withinapproximately one hour. More preferably, at substantially the same timemeans within thirty minutes. Still more preferably, at substantially thesame time means within ten minutes. Still more preferably, atsubstantially the same time means within approximately one minute. Stillmore preferably, at substantially the same time means withinmilliseconds of when the signal is received or generated. Mostpreferably, a substantially same time means that the signal istransmitted or retransmitted at a nearly instantaneous time as it isreceived or generated. Transmitting or retransmitting the signal atsubstantially the same time allows the physician or monitoring serviceto review the subject's physiological and kinetic signals and theenvironmental signals and if necessary to make a determination, whichcould include modifying the subject's treatment protocols or asking thesubject to adjust the sensors.

The receiver (base station, remote communication station, or the like)of various embodiments of the wireless data acquisition system can beany device known to receive RF transmissions used by those skilled inthe art to receive transmissions of data. By way of example but notlimitation, the receiver can include a communications device forrelaying the transmission, a communications device for re-processing thetransmission, a communications device for re-processing the transmissionthen relaying it to another remote communication station, a computerwith wireless capabilities, a PDA with wireless capabilities, aprocessor, a processor with display capabilities, and combinations ofthese devices. Optionally, the receiver can further transmit data toanother device and/or back. Further optionally, two different receiverscan be used, one for receiving transmitted data and another for sendingdata. For example, with the wireless data acquisition system used in thepresent invention, the receiver can be a wireless router thatestablishes a broadband internet connection and transmits thephysiological signal to a remote Internet site for analysis, preferablyby the subject's physician or another clinician. Other examples of areceiver are a PDA, computer, or cell phone that receives the datatransmission, optionally re-processes the information, and re-transmitsthe information via cell towers, land phone lines, or cable to a remoteprocessor or remote monitoring site for analysis. Other examples of areceiver are a computer or processor that receives the data transmissionand displays the data or records it on some recording medium that can bedisplayed or transferred for analysis at a later time. Optionally, twoor more receivers can be used simultaneously. For example, the patientinterface box can transmit signals to a base station receiver thatprocesses and retransmits the signals, as well as a PDA receiver thatdisplays the signals for a clinician to review.

One or more aforementioned sensors are used to develop the data orsignals used in the present invention for, optionally, determining aquantitative level of severity of a subject's sleeping disorder and/orsymptoms, and more preferably to develop a quantitative measurement ofthe level of severity of a subject's sleep apnea.

The signals from the one or more sensors used in various embodiments ofthe present invention are preferably analyzed using a processor andsoftware that can quantitatively estimate or determine the severity ofthe subject's sleeping disorder or symptoms. Using either amicrocontroller of a data acquisition system, a separate computer, basestation or processor, a PDA, a processor on a device for treating thesubject's sleeping disorder or a combination of these processors, theseverity of the subject's sleeping disorder and/or symptoms includingapneas is determined and is used at least in part to regulate thephysical or chemical treatment of the subject. Also optionally, the oneor more sensors used in the system of the present invention can also betethered to a computer, base station, cell phone, a PDA or some otherform of processor or microprocessor.

The processor or microprocessor of various embodiments of the presentinvention can be part of a remote communication station or base station.The remote communication station or base station can also be used onlyto relay a pre- or post-processed signal. Preferably, the remotecommunication station or base station can be any device known to receiveRF transmissions such as those transmitted by the wireless dataacquisition system described herein. The remote communication station orbase station by way of example but not limitation can include acommunications device for relaying the transmission, a communicationsdevice for re-processing the transmission, a communications device forre-processing the transmission then relaying it to another remotecommunication station, a computer with wireless capabilities, a PDA withwireless capabilities, a processor, a processor with displaycapabilities, and combinations of these devices. Optionally, the remotecommunication station can further transmit data both to another deviceincluding the subject's treatment device and/or back. Furtheroptionally, two different remote communication stations can be used, onefor receiving transmitted data and another for sending data. Forexample, with the sleep diagnosis and treatment system of the presentinvention, the remote communication system of the present invention canbe a wireless router, which establishes a broadband internet connectionand transmits the physiological signal to a remote internet site foranalysis, preferably for further input by the subject's physician oranother clinician. Another example is where the remote communicationsystem is a PDA, computer or cell phone, which receives thephysiological data transmission, optionally re-processes theinformation, and re-transmits the information via cell towers, landphone lines, satellite, radio frequencies or cable to a remote site foranalysis. Another example is where the remote communication system is acomputer or processor, which receives the data transmission and displaysthe data or records it on some recording medium, which can be displayedor transferred for analysis at a later time.

The quantitative method for estimating or determining the severity ofthe subject's sleeping disorder or symptoms is preferably accomplishedby using signals or data from the one or more sensors described herein.More preferably, this quantitative method is accomplished in real-time,allowing the subject's symptoms to be treated as they occur. Byreal-time it is meant that the quantitative diagnosis step isaccomplished predictively or within a short period of time aftersymptoms occur which allows for immediate treatment, thereby moreeffectively reducing the health affects of such disorder while at thesame time also minimizing side effects of the treatment chosen. Byreal-time, preferably the diagnosis is accomplished within 24 hours ofreceiving the signals from the one or more sensors on the subject, morepreferably within 8 hours, even more preferably within 4 hours, stilleven more preferably within 1 hour, still even more preferably within 20minutes, still even more preferably within 5 minutes, still even morepreferably within 1 minute, still even more preferably within 10seconds, still even more preferably within 1 second, still even morepreferably within 0.1 seconds and most preferably within 0.01 seconds.

Various algorithms known to those skilled in the art are used to filterout noise from the signal or data, and to then quantify the level ofseverity of the subject's sleeping disorder or symptoms. This filtereddata is then is preferably analyzed using the techniques described inthe following paragraph In addition to these sleeping disorder data orsignal analysis techniques various controller schemes can be used.

Various sleeping disorders have symptoms that can be predicted based onvarious combinations of physiological signals or data. Variousembodiments of the present invention include the approach to identifyingthese symptoms prior to onset by identifying various characteristicshifts in the power spectrum of the sensors being used to monitor thesephysiological conditions. This characteristic shift in these signals ordata can be identified and used to trigger an actuator on the physicalor chemical treatment device(s) to provide for delivery of a certainlevel of treatment. The various embodiments of the present inventioninclude but are not limited to the following signal-processingtechniques that are utilized to predict the onset of these symptoms.These are: (i) the standard deviation technique, (ii) a recursively fitARMAX system identification model, (iii) the Short-Time FourierTransform (SFFT) technique, and (iv) time-frequency signal analysis witha variety of different kernels. The present invention would also includeother on-line signal processing algorithms known to those skilled in theart, such as wavelet analysis, which is similar to time-frequencyanalysis with a particular kernel function, to identify the shift inpower spectrum associated with imminent flow separation that isdiscussed herein.

The standard deviation technique operates on the principle that there isan increase in pressure fluctuation as the flow begins to separate fromthe surface of an airfoil, due to either increasing angle of attack orunsteady flow. A sharp increase in the standard deviation of pressuredata is observed immediately prior to stall. To trigger the deploymentthe flow effectors and initiate fluid flow control, a threshold standarddeviation can be calculated for each pressure sensor and programmed intothe control strategy.

The second embodiment of a method to identify the shift in measuredpower spectrum of the signal from the pressure transducer to identifystall utilizes a recursively identified system model, particularly anAuto-Regressive Moving Average (ARMA) model. Advantageously, thecontroller is the ORICA™ controller, an extended horizon, adaptive,predictive controller, produced by Orbital Research, Inc. and patentedunder U.S. Pat. No. 5,424,942, which is incorporated herein byreference. The ARMA recursive identification method attempts to fitspecific models to the measured data or signals. Evaluation of this datareveals distinct, identifiable model order shifts based, which can beused to actuate the treatment device at various levels. Further analysisof the frequency spectrum of the physiological data related to varioussleeping disorders reveals recognizable changes in this data or signals.This clear characterization alongside the model order shifts allows theORICA identifier to classify discrete models based upon variousphysiological conditions of the subject, thus allowing preciselycontrolled treatments to be delivered to the subject or patient. Asimple function minimization based upon the error associated with eachmodel will enable adaptive model selection for the subject'sphysiological condition. As the subject's physiological conditions movestoward various critical conditions or symptoms, the model with the bestfit to the data will shift into a higher order model. This model shiftforetells the onset of the symptom. A second sub-method of identifyingimpending symptoms using the ARMA and other related models is to trackthe poles of the identified system model based on the subject over time.As the subject's physiological condition moves toward certain designatedcritical symptoms, the poles of the identified system model will movetoward a condition of symptom onset, thereby indicating to the controlsystem that certain critical symptoms are impending. Either of these twosignal identification techniques based on fitting a mathematical modelto the system can be utilized to predict the onset of the subject'ssymptoms. The ARMA model can be adapted to resemble other canonicalmodel forms thereby demonstrating similarity to other systemidentification methods based on Kalman filtering and similar approaches.

A third embodiment of a method for quantifying the power spectrummeasured by the one or more sensors is by using Short-Time FourierTransforms (STFT). A Discrete Fourier transform (DFT), and itsnumerically efficient complement the Fast Fourier Transform (FFT), bothprovide frequency information of a digitized signal or data from thesensors. The DFT and FFT both assume that the signal that is beingmeasured is stationary in time. However, in the case of the subjectbeing tested and treated, the measured signal or data is not stationaryin time, which means a typical DFT/FFT approach is inapplicable.However, for short time periods the signal maybe considered to bestationary. Therefore, it is possible to estimate the mean powerspectrum by segmenting the physiological data or signals into epochslasting anywhere from 0.1-5 seconds each, and then applying adiscrete-time Fourier transform (DFT) to the windowed data. The DFT isused to calculate the power spectrum of the signal for that epoch. Thenthe spectral mean and median density are calculated from the powerspectrum of the signals from each epoch. Using this method it ispossible to identify specific frequency content in the data. As thesubject begins to experience the onset of various critical symptoms, thefrequency spectrum of the measured and analyzed data will shift, whichindicates to the control system that the symptom is beginning.

A fourth embodiment of a signal processing method which can provideindications to the control system that various symptoms are impending,to enable either actuation of the treatment device, is to analyze thesensor data using a time-frequency transform. A time-frequency transformenables both frequency resolution and estimation stability for highlynon-stationary signals, which typifies some types of such as some of thedata or signals related to various physiological conditions. This isaccomplished by devising a joint function of both time and frequency, adistribution that describes the energy and density of a signalsimultaneously in both time and frequency. The general form of thetime-frequency transform is given by the following

${P\left( {t,w} \right)} = {\frac{1}{4\;\Pi^{2}}{\int{\int{\int{e^{{{- j}\;\theta\; t} - {j\;{\tau\omega}} + {j\;\theta\; u}}{{\phi\left( {\theta,t} \right)} \cdot {s^{*}\left( {u - {\frac{1}{2}\tau}} \right)}}{s\left( {u + {\frac{1}{2}\tau}} \right)}d\; u\mspace{11mu} d\;\tau\mspace{11mu} d\;\theta}}}}}$

This transform can be used to calculate instantaneous power spectra of agiven signal. The actual transformation distribution is selected bychanging the kernel, Φ(θ,τ). The function [e−1] is interesting since itis possible to identify any distribution invariant to time and frequencyshifts by means of its kernel, and the properties of the kernel arestrictly related to the properties of the distribution, given by [e−1].

The diagnostic device of the present invention is used to provide anoutput which is then used either automatically to adjust the treatmentdevice or by a clinician or the subject to adjust the device whichprovides the physical or chemical treatment device which is another partof the system of the present invention. There are clearly manyembodiments of the present invention, and we will attempt to describe afew herein.

Also optionally, the signals or data received from the sensors throughthe data acquisition system can be used to train the treatment ortherapeutic device. During a titration or adjustment period the (rich)diagnostic data can be used to train the treatment or therapeutic deviceto recognize more detailed physiological symptoms or signs of a sleepingdisorder, or more particularly a sleep disorder by correlating the morerobust or rich diagnostic data collected with the data acquisitiondevice with the more limited sensor data from the therapeutic ortreatment device. For example, certain conditions which routinely arerecognized by a number of sensors can be correlated to the signature ofthe more limited data from the sensors on the therapeutic or treatmentdevice. For instance, while a central sleep apnea is best recognized bya respiratory effort belt and pulse oximetry. Data from a diagnosticperiod of time can be compared with the sensor data from the treatmentdevice to determine the signature from such data that indicates acentral apnic event occurred. Preferably, the treatment device caninclude a neural network as part of its control mechanism which allowsthe treatment device to correlate the limited sensor data with the morerobust data from the diagnostic period. Optionally, the treatment devicecan further include a library of events recorded from one or moresubjects that allow for more accurate control of the treatment device,and more effective treatment of the subject.

Various embodiments of the present invention include a treatmentinterface device comprising at least one electronic component forreceiving a signal transmitted from the data acquisition system,optionally processing the signal from the data acquisition system, andretransmitting the signal from the data acquisition system ortransmitting a signal based at least in part on at least one of thesignals from the data acquisition system. The treatment interface deviceoperates essentially as part of the data acquisition system, with theexception that it also transmits to a treatment device (i.e., a PAP orCPAP device). Preferably, the treatment interface device receives asignal from a component of the data acquisition system and transmits acommand signal to the PAP or CPAP device. Like a component of the dataacquisition system, the treatment interface device preferably contains atransmitter and a receiver. More preferably, the treatment interfacedevice contains a wireless receiver and/or a wireless transmitter. Thetransmissions sent and received by the treatment interface device do notnecessarily use the same method. For example, the treatment interfacedevice could include both a wireless receiver to receive wirelesstransmissions from the data acquisition system and a USB transmitter totransmit command signals to the PAP or CPAP device. Optionally, thetreatment interface device also contains a receiver or transceiver toreceive data from the PAP or CPAP device. Such data could include, forexample, PAP or CPAP device status information (ex., whether the deviceis on or off, error codes, blower speed, etc.), fluid characteristics ofthe pressurized gas delivered to the patient (ex., airflow, airpressure, humidity, etc.), and the like.

The treatment interface device also preferably contains a processor.Preferably, the treatment interface device uses a processor to executean algorithm for titrating or adjusting the PAP or CPAP device. Thetreatment interface device processor can be used to relate all thereceived signals (from the subject, the environment, and the PAP or CPAPdevice) to each other, and to predict or determine the next appropriatetreatment setting. For example, the treatment interface device couldreceive a pulse oximetry signal, a thoracic effort signal, and a roomtemperature signal from a data acquisition system, and an airflow signalfrom the PAP or CPAP device. The treatment interface device processorwould then use the signals to calculate the next appropriate treatmentsetting. For example, the treatment interface device processor could usethe airflow, pulse oximetry signal, thoracic effort, and roomtemperature to determine that the PAP pressure should be increased by 2cm H₂O. The treatment interface device processor would then create acommand signal to instruct the PAP device to increase the pressureappropriately. The treatment device processor is preferably capable ofexecuting closed-loop titration, thereby automatically determining a setof final treatment values for the treatment device. The set of finaltreatment values for the treatment device are the parameters programmedinto the treatment device (i.e., the PAP or CPAP), which the treatmentdevice uses during operation. Once the set of final treatment values areprogrammed into the treatment device, the treatment device will continueto operate according to the set of final treatment values. For example,if the treatment device were a CPAP device, the set of final treatmentvalues would be the gas pressure delivered to the patient. Similarly, ifthe treatment device were a bi-PAP device, the set of final treatmentvalues would be the inspiration gas pressure and the expiration gaspressure. The set of final treatment values depends on both the type oftreatment device and the results of the titration process. Essentially,the titration process is designed to determine the set of finaltreatment values for a given treatment device and a given subject. Thetreatment interface device processor is preferably capable of using avariety of techniques to conduct the titration, including but notlimited to lookup tables, relationship algorithms, neural networks,wavelets, fast-Fourier transforms, and the like. Various embodiments ofthe present invention include a treatment interface device capable ofautomatically conducting titration of the treatment device. In thiscase, the treatment device interface uses closed-loop control to run thetitration, determine the set of final treatment values, and program thetreatment device to deliver the set of final treatment values.Optionally, the set of final treatment values is sent to a clinician forapproval. Various other embodiments of the present invention include atreatment interface device capable of using closed-loop control to runthe titration and determine the set of final treatment values, but thetreatment interface device is not capable of independently programmingthe treatment device. In this case, a clinician must review the set offinal treatment values, approve or adjust them, and then program thetreatment device. Various other embodiments of the present inventioninclude a treatment interface device that is only capable of conductingan open-loop titration. In this case, a clinician must conduct thetitration, determine the set of final treatment values, and program thetreatment device. Thus, the treatment interface device only provides theclinician with a means to control the treatment device and obtaininformation from it.

Various embodiments of the present invention include a PAP or CPAPdevice comprising an electrical connection or component for receiving aretransmitted or transmitted signal. The PAP or CPAP device can be anydevice known in the art that is capable of delivering a flow of gas tothe subject and is capable of being titrated or adjusted. The PAP orCPAP device may receive a signal containing command information only.For example, the PAP or CPAP device could receive a command signal toincrease the pressure of gas delivered to the subject, to decrease thegas pressure, or to cease operations. Optionally, the device may receivea signal containing data requiring further processing by the PAP or CPAPdevice. For example, the data acquisition system could transmit a signalcontaining pulse oximetry and respiration characteristics, which the PAPor CPAP device further processes to relate to an internal airflow signaland determine the next appropriate gas pressure setting.

The PAP or CPAP device could contain any component known in the art toreceive the signals sent from the data acquisition system. For example,if the data acquisition system provides a signal transmitted via. USB,the PAP or CPAP device could contain a receiver component for obtainingthe transmitted USB signals. Optionally, the PAP or CPAP device may be awireless receiver. In this case, for example, the PAP or CPAP devicewirelessly receives the signals from a transmitting component of thedata acquisition system (the patient interface box, the base station, orother component capable of wirelessly transmitting signals), optionallyprocesses the signal, and makes an adjustment to the flow of gasprovided to the subject. Further optionally, the PAP or CPAP devicecontains a component for receiving a signal transmitted from a remotemonitoring station. In this case, for example, a remote monitor receivesdata from the data acquisition system, determines the next appropriategas pressure setting, and transmits the setting to the PAP or CPAPdevice.

Various embodiments of the present invention include a PAP or CPAPdevice capable of processing the received signal. Such processing can beused to relate the received signals to each other and any additionalsignals collected by the PAP or CPAP device itself. For example, the PAPor CPAP processor could receive a pulse oximetry signal from a dataacquisition system, an airflow signal from the PAP or CPAP deviceitself, and a signal to increase the gas pressure from a remote monitor.The PAP or CPAP processor would then relate the signals to each other,thereby creating a lookup table of values or a more sophisticatedrelationship algorithm. The PAP or CPAP processor is optionally capableof creating a neural network and training the network with datacollected from an individual subject over several nights. Such a neuralnetwork could “teach” the PAP or CPAP device to accurately predict apneaevents (confirmed with physiological sensors) based only on gas flowcharacteristics. In this way, the PAP or CPAP device can continue tooperate correctly based on gas flow characteristics alone, and thephysiological sensors become redundant.

Various embodiments of the present invention include the step ofprocessing or pre-processing the signals received from the sensorsattached to the subject. The processor or preprocessor of variousembodiments of the present invention can be independent, or combinedwith any other component. For example, a processor or preprocessor couldbe a part of the patient interface box, base station, treatmentinterface, or PAP or CPAP device. Optionally, the processor orpreprocessor could be distributed between two or more components of thedevice. Optionally, preprocessing can correct artifacts, derive a totalsleep time, derive a snore signal, filter a signal, or compress and/orencrypt the data for transmission as described above. Preferably, thepreprocessing step corrects for artifacts present in the sensor signals.Optionally, a step of more powerful processing can perform one or moreof the preprocessing functions. Further optionally, more powerfulprocessing can determine the appropriate pressure to be delivered by thePAP or CPAP to the subject. Further optionally, more powerful processingcan determine whether the patient has central or obstructive sleepapnea. For example, in the case of CSA, the processing can provide arecommendation to stop CPAP treatment and use another treatment specificto CSA.

Various embodiments of the present invention include a system capable ofdetermining the location of obstructions in the airways of subjects.This feature is helpful because one OSA treatment modality is surgicalprocedures that rely on excising part of the tissue causing theobstruction. In these embodiments, the system detects an obstructiveapnea event, and then determines the location of the obstruction usingacoustic reflectance methods. A sound wave created by an oscillatingpiston (tuning fork, membrane, loudspeaker, and the like), an aperture(whistle, reed, and the like), or any other method of producing a soundof known frequency is introduced into the flow of pressurized gasdelivered to the patient. The sound wave can be generated inside the PAPor CPAP device, inside the mask, or at any other suitable location.Preferably, the sound is outside the audible frequency range to minimizedisturbance to the subject. A pressure transducer in the system willthen receive the pressure signals generated by the echo waves bouncingback from the obstructed wall inside the airways. Effectively, the dataacquisition system will “listen” to the echoes coming back from insidethe subject's airways. Using the delay between the known time of theoriginal sound wave and the detected echo, the system can calculate thelocation of the obstruction. Measuring the pressure of the reflectedsound wave can allow the system to distinguish between the obstructionand other anatomical features of the airway. It is expected that theobstruction site will generate the biggest pressure amplitude, therebydifferentiating it from other nearby structures. Also, the system couldbe configured to “listen” for charges in frequencies or detect an echosignature to determine the density of the tissue the sounds waves arereflected from. Thus allowing for the determination between hard andsoft tissue.

Signal quality of the signals from all the sensors can be affected bythe posture and movement of the subject. For methods of the presentinvention, it is important to reduce motion artifacts from the sensorplacement. Errors in the form of noise can occur when biopotential dataacquisition is performed on a subject. For example, a motion artifact isnoise that is introduced to a biopotential signal via motion of anelectrode placed on the skin of a subject. A motion artifact can also becaused by bending of the electrical leads connected to any sensor. Thepresence of motion artifacts can result in misdiagnosis, prolongprocedure duration and can lead to delayed or inappropriate treatmentdecisions. Thus, it is imperative to remove motion artifact from thebiopotential signal to prevent these problems from occurring duringtreatment.

The present method of collecting signals from a subject includes a meansof reducing motion artifacts. When physiological electrodes are used,preferably they are used with conductive gels or adhesives. Morepreferably, dry electrodes are used with or without conductive gels oradhesives. Still more preferably, the device's firmware and/or softwareuses body motion information for artifact correction. Most preferably, acombination of the above methods is used.

The most common methods for reducing the effects of motion artifacts insensors such as electrodes have focused on skin deformation. Thesemethods include removing the upper epidermal layer of the skin byabrasion, puncturing the skin near the electrode, or measuring skinstretch at the electrode site. The methods for skin abrasion ensure goodelectrical contact between the electrode and the subject's skin. In thismethod, an abrasive pad is mechanically rotated on the skin to abradethe skin surface before electrode placement. Similarly, medicalelectrodes have been used with an abrading member to prepare the skinafter application of the electrode whereby an applicator gun rotates theabrading member. Methods of skin preparation that abrade the skin with abundle of fibers have also been disclosed. These methods provide a lightabrasion of the skin to reduce the electrical potential and minimize theimpedance of the skin, thereby reducing motion artifacts.

Skin abrasion methods can cause unnecessary subject discomfort, prolongprocedure preparation time and can vary based on operator experience.Furthermore, skin abrasions methods can lead to infection, and do notprovide an effective solution to long term monitoring. Dry physiologicalrecording electrodes could be used as an alternative to gel electrodes.Dry physiological recording electrodes of the type described in U.S.Pat. No. 7,032,301 are herein incorporated by reference. Dryphysiological electrodes do not require any of the skin abrasiontechniques mentioned above and are less likely to produce motionartifacts in general.

Although the above-mentioned methods reduce motion artifacts, they donot completely eliminate them and they are less effective for sensorsthat do not measure a biopotential signal, such as respiratory effortbelts, flow meters, environmental sensors, and the like. The inventionpreferably incorporates a step to more completely remove motion andother artifacts by firmware and/or software correction that utilizesinformation collected preferably from a sensor or device to detect bodymotion, and more preferably from an accelerometer. In certainembodiments of the present invention, a 3-D accelerometer is directlyconnected to the data acquisition system. The data acquisition systemreceives signal inputs from the accelerometer and at least one set ofother physiological or kinetic signals. The microprocessor appliesparticular tests and algorithms comparing the two signal sets to correctany motion artifacts that have occurred. The processor in one embodimentapplies a time synchronization test, which compares the at least one setof physiological or kinetic signal data to the accelerometer signal datasynchronized in time to detect motion artifacts and then remove thoseartifacts. Alternatively, the processor may apply a more complicatedfrequency analysis. Frequency analysis preferably in the form of waveletanalysis can be applied to the accelerometer and at least one set ofphysiological or kinetic signals to yield artifact detection. Yetanother alternative is to create a neural net model to improve artifactdetection and rejection. This allows for the system to be taught overtime to detect and correct motion artifacts that typically occur duringa test study. The above illustrations are only examples of possibleembodiments of the present invention and are not limitations. Theaccelerometer data need not be analyzed before wireless transmission; itcould be analyzed by a base station, computer, or the like aftertransmission. As should be obvious to those skilled in the art, a 2-Daccelerometer or an appropriate array of accelerometers could also beused. Gyroscopes could be used as well for these purposes.

Sensors can be used to detect motion of the subject's body or a portionof the subject's body. The motion information can then be used to detectthe posture and movement of the subject. This motion information mayindicate that the subject has a sleeping disorder unrelated tobreathing, such as restless legs syndrome (RLS) or other parasomnia. Themotion information can be used to correct for error in the form of noiseor motion artifact in the other sensor channels. To detect motion,various embodiments of the present invention include sensors, devices,and methods of determining the posture and movement of the subject. Thisinformation can be used when analyzing the physiological signals. Theposture and movement of the subject is preferably determined by signalsreceived from an accelerometer or an array of two or moreaccelerometers. Accelerometers are known in the art and are suitable foruse as motion-monitoring units. Various other types of sensors can beadditionally or alternatively used to sense the criteria (e.g.,vibration, force, speed, and direction) used in determining motion. Forparticularly low power designs, the one or more sensors used can belargely mechanical.

Body movement of the subject will result in a high amplitude signal fromthe accelerometer. The data acquisition system can also monitor thesensor signals for any indication that the subject has moved, forexample from a supine position to an upright position. For example, theintegrated velocity signal computed from the vertical accelerationcomponent of the sensor data can be used to determine that the subjecthas just stood up from a chair or sat up in bed. A sudden change in thevertical signal, particularly following a prolonged period with littleactivity while the subject is sleeping or resting, confirms that aposture-changing event occurred. The data acquisition system can alsomonitor the sleep-wake cycle of the patient. Sleep-wake data will beused to determine the total sleep time for the calculation of theapnea/hypopnea index and other sleep related indices.

In addition, a video camera can be used to detect subject movement andposition, and the information then used to correct any artifacts thatmay have arisen from such movement. Preferably, the camera is a digitalcamera. More preferably, the camera is a wireless digital camera. Stillmore preferably, the camera is a wireless digital infrared camera.Preferably, the video acquired from the camera is processed so that thesubject's movement and position are isolated from other information inthe video. The movement and position data that are acquired from thevideo is then preferably analyzed by software algorithms. This analysiswill yield the information needed to make artifact corrections of thephysiological signals. Optionally, alternative analysis of the videosignal can indicate additional sleeping disorders, such as restless legssyndrome (RLS), sleepwalking, or other parasomnia.

One specific embodiment of the present invention using video subjectmovement detection involves the use of specially marked electrodes. Theelectrodes can be any appropriate electrode known in the art. The onlychange to the electrode is that they preferably have predetermined highcontrast marks on them to make them more visible to the video camera.These marking could be manufactured into the electrodes or simply be asticker that is placed on the back of the electrodes. These markingsenable the video system to accurately distinguish the electrodes fromthe rest of the video image. Using the markers on each visibleelectrode, the system can calculate of the movement of each individualelectrode, thus allowing for more accurate artifact correction.

In another specific embodiment of the invention, the system can detectsubject movement by monitoring the actual movement of the subject'sbody. Software is applied to the video that first isolates the positionof the subject's body, including limbs, and then continues to monitorthe motion of the subject.

There are numerous advantages to using video over other means ofartifact detection and correction. Foremost, video allows for thecalculation of movement artifacts from each individual electrode withoutthe need for accelerometers. This makes the use of video very costeffective in relation to other available methods. The video also can beused in conjunction with the accelerometer data to correct for motionartifacts, thus increasing the precision and accuracy of the system'smotion artifact correction capabilities.

Current auto-titrating machines adjust PAP or CPAP pressure based onairflow/pressure alone. The advantage of using multiple parameters overjust an airflow or pressure parameter is that the PAP or CPAP can nowconfirm events and differentiate between central apnea and hypopneas andobstructive apneas and hypopneas. For example, when airflow drops,existing commercial systems will “assume” the event is obstructive;however, the current invention will “know” whether it is obstructive orcentral by further investigating two other parameters. If pulse ox dropsbelow 3% and thoracic effort persists, then the apnea/hypopnea isobstructive. If the pulse ox drops below 3% and the thoracic effortceases then the apnea/hypopnea is central. If pulse ox does not drop by3% then the event cannot be considered an hypopnea at all.

It is a benefit for auto-titrating machines to confirm or to knowcentral apneas vs. obstructive apneas, since central events areindicative of more serious cardiovascular problems and, more often thannot, they cannot be properly treated with conventional CPAP treatment.Additional treatment such as oxygen is needed. It is suspected that upto 15% of patients develop central events once they are placed on PAP orCPAP. The development of central events after PAP or CPAP administrationis thought to be generated by a newly discovered and newly createddisease called Complex Sleep Apnea (CompSA), which requires a verydifferent treatment than the traditional CPAP.

The current invention preferably includes at least one treatment devicefor treating central or complex apneas. The treatment devices can eitherbe a traditional PAP or CPAP, or can include various devices forchemical or medical treatment of the subject. The subject may also havetwo or more treatment devices that are titrated at the same time. Forexample, the subject could have a PAP device that is being titrated atthe same time as a functional electrical stimulation (FES) device. Alsothe treatment devices could be used to “train” the subject to giverespiratory effort while asleep. Thus the treatment devices can be usedas a form of therapy instead of being used as a treatment device alone.This could be accomplished in several ways. For example, a FES devicethat stimulates the subject to give respiratory effort could be usedwhile the subject is given supplemental CO₂. This application alsocovers the treatment device for use with these features as well as thetreatment device for use with additional sensors. Preferably, the newCPAP or PAP with a respiratory effort belt is used to detect respiratoryeffort. Some way of measuring respiratory effort is needed since thediagnosis of central and complex apneas requires some indication of thelack of respiratory effort.

The treatment device could include an O₂ tank or source, a CO₂ tank orsource, a medication or chemical reservoir, combinations thereof, andthe like. The supplemental oxygen can be used to alleviate symptoms andadverse affects of central and complex apneas. Supplemental oxygen mayeven be used on obstructive apneas. Another example of chemicallytreating the subject's sleeping disorder would be to have a medicationreservoir where a drug is delivered to the subject in order to treatsymptoms of the sleeping disorder. Preferably, this medication reservoiris placed inline with the airflow of a PAP or CPAP device to deliver anebulized medication or drug to the subject's lungs. Also preferably,the PAP or CPAP device can be used to deliver CO₂ to trigger a breathingresponse to treat specific central apneas. A treatment device thattreats the underlying problems of a subject's central or complex sleepapneas by administrating appropriate substances could be titrated andused in conjunction with the PAP or CPAP device. For example,beta-blockers could be automatically administered to treat improperheart function, thus preventing central apneas from occurring. Of courseother substances could be administered depending on the underlyingpathology of the central or complex apneas. It is often the case thatcentral apneas are caused by some cardiac or neuromuscular pathology.

A method to automatically titrate PAP or CPAP pressure is based on theabove physiological parameters that are specific to the subject. Theshapes of physiological signals often differ between subjects,especially during events such as hypopneas, apneas, upper airwayresistance, central apneas, and others. The ability to wear a portabledata acquisition system or device for a few days will allow the PAP orCPAP to be trained on the physiological signals that are specific tothat subject. This “subject specific” information can then be used tobetter optimize auto-titration since it can now better detect hypopneas,apneas, etc.

Preferably, the titration method of the present invention includes astep whereby the titration analysis runs over a minimum period of time,preferably at least 15 minutes, before pressure adjustment occurs. Thisperiod is needed to make sure pressure is not titrated up or downwithout sufficient confirmation of the event. For example, in the eventa subject holds their breath for whatever reason, perhaps a bad dream,if the adjustments are made quickly a traditional system mayunnecessarily increase pressure because the system has falsely detectedan apnea. This is why it is necessary to wait a sufficient period oftime, so that non-pathogenic irregular breathing does not affect the PAPor CPAP titration.

Various embodiments of the present invention include the step ofconducting PAP or CPAP titration that is attended from a remotelocation. Such remote attendance can be accomplished in several ways,for example by an individual in a remote location (a remote monitor)periodically or continuously viewing the data transmitted from the dataacquisition system, including signals from the sensors and apreprocessed signal or signals based at least in part on at least one ofthe sensors. Remote monitoring can be achieved at various levels,including but not limited to, post-titration approval, titrationapproval, and active titration. Further, each level of monitoring can beeither periodic or continuous, and can incorporate automatic alerts.Several illustrative examples of monitoring are described below.

In a post-titration approval monitoring scheme, the remote monitorreceives a report of the titration process after completion. In thisexample, the subject receives a completely automated titration systemthat independently determines the appropriate pressure of the deliveredgas. While the subject sleeps or attempts to sleep, the systemautomatically adjusts to find the set of final treatment values (i.e.,the optimal gas pressure). Then the PAP or CPAP device programs itselfto continue delivering the set of final treatment values. The systemalso sends the collected data and set of final treatment values to theremote monitor, who reviews the collected data and approves or rejectsthe system's set of final treatment values. If the monitor approves thesystem's set of final treatment values, the subject can return all theequipment other than the PAP or CPAP device and then use the PAP or CPAPdevice for ongoing treatment.

In this scenario, the remote monitor is not actively engaged in thetitration process. This type of monitoring is typically periodic, withthe remote monitor reviewing the data at a single point (after the endof the titration), or at multiple points, for example at the end of eachnight during a multi-night titration. This type of monitoring could alsobe continuous, in that the remote monitor continuously receives datafrom the titration system. Post-titration approval monitoring isgenerally suited to subjects with relatively simple apnea and fewcomplicating factors. Preferably, the review portion of thepost-titration approval monitoring takes place within a few weeks of thetitration night(s). More preferably, the review takes place within oneweek; more preferably within three days; still more preferably withinone day; still more preferably within six hours; still more preferablywithin one hour of the end of the titration nights.

In a titration approval monitoring scheme, the remote monitor receives areport of the titration process after completion. In contrast to thepost-titration approval, however, the remote monitor must approve theset of final treatment values before the PAP or CPAP device isprogrammed to continue delivering that pressure. In this example, thesubject could receive an automated titration system that independentlydetermines the set of final treatment values by automatically adjustingwhile the subject sleeps. The system then sends the collected data andset of final treatment values to the remote monitor, who reviews thecollected data and approves or modifies the system's set of finaltreatment values. If the monitor approves the system's set of finaltreatment values, the remote monitor programs the PAP or CPAP device tocontinue using set of final treatment values. Optionally, the subjectcould receive a semi-automated titration system that periodicallychanges treatment values. The system sends the collected data andcorresponding treatment values to the remote monitor, who reviews allthe data and determines the set of final treatment values. After theremote monitor determines the set of final treatment values, the PAP orCPAP device is programmed to deliver it.

This type of monitoring is typically periodic, with the remote monitorreviewing the data at a single point (after the end of the titration),or at multiple points, for example at the end of each night during amulti-night titration, or several times during the titration nights.This type of monitoring could also be continuous, in that the remotemonitor continuously receives data from the titration system.Preferably, the remote monitor determines the optimal gas pressurewithin one day; still more preferably within six hours; still morepreferably within one hour of the end of the titration nights, and mostpreferably within 20 minutes of the end of the titration.

In an active titration monitoring scheme, the remote monitor receivessignals from the system during the titration phase. Preferably, theremote monitor receives data every hour; more preferably the remotemonitor receives data every twenty minutes; more preferably every fiveminutes; and most preferably the remote monitor receives continuousstreaming data during the titration phase. In contrast to thepost-titration approval and titration approval, the remote monitor isactively engaged in the titration process. In this example ofmonitoring, the subject could receive a titration system that collectsand transmits data to the remote monitor. The remote monitor thenreviews the data and deteiinines the next level of gas pressure for thetitration. The remote monitor transmits the appropriate command to thePAP or CPAP device (ex., to increase or decrease the gas pressure), anddata collection continues until the treatment value requires adjustment.After the remote monitor has completed the titration and determined aset of final treatment values, the PAP or CPAP device is programmed tocontinue using the set of final treatment values. This type ofmonitoring can be periodic, with the remote monitor reviewing the dataat multiple points, for example just before each change in PAP or CPAPgas pressure. This type of monitoring could also be continuous, with theremote monitor continuously receiving and reviewing data.

Other types of remote monitoring can include only monitoring at thebeginning of the titration to assess the quality of the collectedsignals. For example, the subject can set up the titration system, andthe remote monitor can view preliminary data for adequacy. If a sensorhas been improperly placed or incorrectly connected, the remote monitorcan instruct the subject to take remedial action. In this way, theremote monitor can ensure receipt of sufficient and adequate data toperform the titration correctly.

Each level of monitoring can include an alert function wherein themonitor receives alerts of predetermined events. For example, themonitor could be alerted when the subject's oxygen saturation dropsbelow a predetermined threshold, when the PAP or CPAP device isinstructed to deliver a gas pressure over a safety threshold, every timethe system changes the pressure, when an electrode's impedanceincreases, if a sensor malfunctions, or for any other event. The systemcan also be programmed to alert the remote monitor of more complexevents, such as detection of an apnea event after the PAP or CPAP hasreached a defined gas pressure setting, a drop in oxygen concentrationcombined with cessation of thoracic breathing activity, or a sensor hasmoved and no back-up sensors are available. Preferably, the alertfunction is provided in all of the monitoring schemes described above.

Preferably, the remote monitor is capable of communicating with thesubject, subject's assistant, or other individual near the subject. Suchcommunication allows the remote monitor to provide instructions to thesubject, subject's assistant, or other individual near the subject, forexample, to adjust a sensor, close window blinds, remove a source ofnoise, turn off any equipment, or wake the subject. More preferably, theremote monitor is capable of two-way communication with the subject,subject's assistant, or other individual near the subject. Suchcommunication allows the subject, subject's assistant, or otherindividual close to the subject to ask the remote monitor questions, forexample, to clarify instructions.

Various embodiments of the present invention include a step ofmonitoring a subject from a separate monitoring location. Datatransmitted in a remote monitoring application may include, but are notlimited to, physiological data, kinetic data, environmental data, PAP orCPAP device data, audio, and video recording. It is preferable that bothaudio and video communications be components of the envisioned system inorder to provide interaction between the subject and remote monitor.

Preferably, the data is transmitted from a base station to a database orremote monitoring location with a wireless module or card through acellular service provider. The envisioned remote monitoring applicationmay allow for multiple remote monitoring locations anywhere in theworld. Remote data collection to monitoring station configurations mayinclude, but are not limited to one-to-one, one-to-many, many-to-one, ormany-to-many. The envisioned system may include a central server, orgroup of servers that can collect data from one or more remote sites andoffer delivery to multiple viewing clients.

It is preferable that the remote monitoring application employ awireless network link between the subject and caregiver such as acellular wireless network. Other wireless techniques include but are notlimited to satellite communications, direct radio, infrared links, andthe like. Data transmission through a wired network such as dial-upmodem, digital subscriber line (DSL), or fiber-optic, while lesspreferable, can also be used. Bandwidth management facilities will beemployed to facilitate remote monitoring in low-speed communicationnetworks. Several data compression techniques are envisioned to maximizesystem utilization in low-bandwidth environments.

The envisioned remote monitoring step will require data processing,storage, and transmission. This step may be completed or accomplished inone or more modules of the data acquisition system. The preferredembodiment realizes the remote system as two separate components with apatient interface module that can collect, digitize, store, and transmitdata to a base station module that can store, process, compress,encrypt, and transmit data to a remote monitoring location. Thepreferred embodiment of the remote monitoring system will consist ofseveral system modules. A patient interface module will collectphysiological and kinetic data from the subject and transmit the signalsto a base station module. The base station module will receive thephysiological and kinetic data from the patient interface module, andwill also preferably directly connect to any environmental sensors andany PAP or CPAP sensors. The base station module will preferably consistof an embedded computer equipped with a cellular wireless data/voicecard and a night-vision video acquisition system. The embedded computerwill collect, analyze, compress, and encrypt the data and relay them toone or more viewing caregivers. The remote monitoring systems willbroadcast their dynamically assigned IP addresses to a dedicated addressserver, which will be used for lookup by the viewing caregivers.Computer software used by caregivers will enumerate each remotemonitoring system in the field using the aforementioned address serverand allow caregivers to select one or more for monitoring. The softwarewill have the ability to control data acquisition including start andstop of acquisition, as well as system reconfiguration.

The software preferably will also provide real-time control over thedisplay of data including page width, amplitude, color, montage, and thelike. The software will also provide both real-time video and audiocommunication with the subject using dual services from the cellularcard. Video will preferably be transmitted through the data connection,and audio will preferably be transmitted through the voice connection.

While the equipment and methods used in the various embodiments of thepresent invention can be used in rooms or buildings adjacent to thesubject's sleeping location, due to the equipment's robust nature thesemethods are preferably performed over greater distances. Preferably, thesubject's sleeping location and the remote locations, for example thelocation of the remote monitor, are separate buildings. Preferably, thesubject's sleeping location is at least 1 mile from the remotelocation(s) receiving the data; more preferably, the subject's sleepinglocation is at least 5 miles from the remote location(s) receiving thedata; even more preferably, the subject's sleeping location is at leasttwenty miles from the remote location(s) receiving the data; still morepreferably, the subject's sleeping location is at least fifty miles fromthe remote location(s) receiving the data; still even more preferably,the subject's sleeping location is at least two hundred-fifty miles fromthe remote location(s) receiving the data; more preferably, thesubject's sleeping location is in a different state from the remotelocation(s) receiving the data; and most preferably, the subject'ssleeping location is in a different country from the remote location(s)receiving the data.

Various embodiments of the present invention include the step ofevaluating the received signals to determine if they are adequate forlater analysis. This step can be performed or accomplished a number ofways. In the simplest form, the signal can be evaluated once just priorto the start of the sleep study. In another form, the signal isevaluated periodically during the study to determine its quality.Preferably, the signal(s) are evaluated both at the start of the studyand periodically during the study. Most preferably, the signals areevaluated at the beginning of the study and continuously during thestudy. If the signals are evaluated for adequacy, preferably the subjectcan be contacted to adjust the sensor as necessary. In this way,corrective action can adjust an inadequate signal to increase the valueof the sleep study data and enable later analysis.

The data collected for the sleep analysis conducted under the variousmethods of the present invention can be viewed by any number of medicalpersonnel and the subject themselves, if appropriate. Preferably, thedata is available to a sleep technician, to a doctor making theanalysis/diagnosis based on the data, and others involved in thesemethods. This data can be reviewed at multiple locations including butnot limited to the doctor's home or office, or anywhere else the doctoror other individuals associated with the analysis/diagnosis have accessto the internet or a intranet.

Referring now to the drawings and, in particular to FIG. 1, there isshown a block diagram of the present invention. An external input 12from sensor 14 is input to signal processing module 16. Although, onesensor 14 and one external input 12 are shown, the signal processingmodule 16 is capable of accepting multiple external inputs 12 frommultiple sensors 14. The signal processing module 16 generates a signal18 encoded with data corresponding to the external input 12. The signalprocessing module 16 transmits the signal 18 by wireless means to a basestation 40. In FIG. 1, the wireless means is shown as radio frequency(RF). In this case, the signal processing module generates a radiofrequency signal 18 by frequency modulating a frequency carrier andtransmits the radio frequency signal through module antenna 20. The basestation 40 receives the radio frequency signal 18 through base antenna42, demodulates the radio frequency signal 18, and decodes the data. Itis understood that other wireless means can be utilized with the presentinvention, such as infrared and optical, for example. Although onemodule antenna 20 and one base antenna 42 is shown in this embodiment,it is understood that two or more diversity antennas can be used and areincluded in the present invention. An external programming means 60,shown in FIG. 1 as a personal computer, contains software which is usedto program the signal processing module 16 and the base station 40through data interface cable 62. The data interface cable 62 isconnected to the base station 40 and signal processing module 16 byrespective connectors 64. The same data interface cable 62 or twodifferent interface cables 62 can be used, one for the base station 40and one for the signal processing module 16. The signal processingmodule 16 and the base station 40 can be programmed by connecting a datainterface cable 62 between it and an external programming means 60 or byradio frequency (or other type) of signals transmitted between a basestation 40 to the signal processing module 16 or to another base station40. RF signals, therefore, can be both transmitted and received by bothsignal processing module 16 and base station 40. In this event thesignal processing module 16 also includes a module receiver 29 while thebase station 40 also includes a base transmitter 84, in effect makingboth the signal processing module 16 and the base station 40 intotransceivers. In addition, the data interface cable 62 also can be usedto convey data from the base station 40 to the external programmingmeans 60. If a personal computer is the external programming means 60,it can monitor, analyze and display the data in addition to itsprogramming functions. The base receiver 80 and module receiver 29 canbe any appropriate receivers, such as direct or single conversion types.The base receiver 80 preferably is a double conversion superheterodynereceiver while the module receiver 29 preferably is a single conversionreceiver. Advantageously, the receiver employed will have automaticfrequency control to facilitate accurate and consistent tuning of theradio frequency signal 18 received thereby.

Referring now to FIG. 2, there is shown a block diagram of the signalprocessing module 16 with the sensor 14 and the module antenna 20. Thesignal processing module 16 comprises input means 22, analog-to-digital(A/D) means 24, a module microcontroller 26 with a nonvolatile memory,advantageously, an EEPROM 261, a module transmitter 28, a modulereceiver 29 and a module power supply 30. Although the module antenna 20is shown externally located from the signal processing module 16, it canalso be incorporated therein. The module antenna 20 may be a printedspiral antenna printed on a circuit board or on the case of the signalprocessing module 16 or other type of antenna. A module power supply 30provides electrical power to the signal processing module 16 whichincludes the input means 22, A/D means 24, module microcontroller 26module transmitter 28 and module receiver 29.

The input means 22 is adjustable either under control of the modulemicrocontroller 26 or by means of individually populatable componentsbased upon the specific external input 12 characteristics and rangeenabling the input means 22 to accept that specific external input 12.For example, if the input is a 4-20 mA analog signal, the input means 22is programmed by the module microcontroller 26 and/or populated with thecomponents needed to accept that range and characteristic of signals. Ifthe input characteristics change the programming and/or componentschange accordingly but the same platform circuit board design isutilized. In other words, the same platform design is utilizednotwithstanding the character, range, or quantity. (number of externalinputs 12) [up to a predetermined limit] of the input. For example,bioelectric signals such as EEG, EMG, EKG, and EOG have typicalamplitudes of a few microvolts up to a few tens of millivolts. For agiven application, a specific frequency band of interest might be from0.1 Hz to 100 Hz, whereas another application may require measurement ofsignals from 20 Hz to 10 KHz. Alternatively, measurement of vital signssuch as body temperature and respiration rate may deal with signals in arange of +5 volts, with a frequency content from DC (0 Hz) to 20 Hz. Forother applications such as industrial process monitoring, theinformation of interest may be contained in the signal as a current,such as a 4 to 20 mA current loop sensor, or it may take the form ofresistance, impedance, capacitance, inductance, conductivity, or someother parameter, The present invention provides a single device formeasuring such widely disparate signal types and presents distincteconomic advantages, especially to small enterprises such as a medicalclinic located in a rural area, which would be empowered by thisinvention to conduct tests which would otherwise have required subjecttravel to a large medical center, with all the attendant cost thereof.

This is possible due to the selectively adaptable input means 22 and A/Dmeans 24, the frequency agile module transmitter 28 and base transmitter84, and the programmability of the module microcontroller 26 and EEPROM261. One universal platform design then can be utilized for allapplications. In addition, the signal processing module can comprisemultiple copies of the input means 22 and the A/D means 24. Cost savingscan be achieved by multiplexing at several different points in the inputmeans 22 and the A/D means 24 allowing hardware to be shared amongexternal inputs 12.

After receipt by the input means 22, the external input 12 is inputtedto the A/D means 24. The A/D means 24 converts the input to a digitalsignal 32 and conditions it. The A/D means 24 utilizes at least oneprogrammable A/D converter. This programmable A/D converter may be anAD7714 as manufactured by Analog Devices or similar. Depending upon theapplication, the input means 22 may also include at least one low noisedifferential preamp. This preamp may be an INA126 as manufactured byBurr-Brown or similar. The module microcontroller 26 can be programmedto control the input means 22 and the A/D means 24 to provide specificnumber of external inputs 12, sampling rate, filtering and gain. Theseparameters are initially configured by programming the modulemicrocontroller 26 to control the input means 22 and the A/D means 24via input communications line 35 and A/D communications line 36 basedupon the input characteristics and the particular application. If theapplication changes, the A/D converter is reconfigured by reprogrammingthe module microcontroller 26. In this manner, the input means 22 andthe A/D means 24 can be configured to accept analog inputs of 4-20 mA,+/−5 volts, +/−15 volts or a range from +/−microvolts to millivolts.They also can be configured to accept digital inputs, for detection ofcontact closure, for example.

The module microcontroller 26 controls the operation of the signalprocessing module 16. In the present invention, the modulemicrocontroller 26 includes a a serial EEPROM 261 but any nonvolatilememory (or volatile memory if the signal processing module remainspowered) can be used. The EEPROM 261 can also be a separate componentexternal to the module microcontroller 26. Advantageously, the modulemicrocontroller 26 may be PIC16C74A PIC16C74B or a PIC16C77 bothmanufactured by MicroChip, or an Amtel AT90S8515 or similar. The modulemicrocontroller 26 is programmed by the external programming means 60through the connector 64 or through radio frequency signal from the basestation 40. The same module microcontroller 26, therefore, can beutilized for all applications and inputs by programming it for thoseapplications and inputs. If the application or inputs change, the modulemicrocontroller 26 is modified by merely reprogramming. The digitalsignal 32 is inputted to the module microcontroller 26. The modulemicrocontroller 26 formats the digital signal 32 into a digital datastream 34 encoded with the data from the digital signal 32. The digitaldata stream 34 is composed of data bytes corresponding to the encodeddata and additional data bytes to provide error correction andhousekeeping functions. Advantageously, the digital data stream 34 isorganized in data packets with the appropriate error correction databytes coordinated on a per data packet basis. These packets canincorporate data from a single input channel or from several inputchannels in a single packet, or for some applications may advantageouslyinclude several temporally differing measurements of one or a pluralityof input channels in a single packet. The digital data stream 34 is usedto modulate the carrier frequency generated by the transmitter 28.

The module transmitter 28 is under module microcontroller 26 control.The module transmitter 28 employs frequency synthesis to generate thecarrier frequency. In the preferred embodiment, this frequency synthesisis accomplished by a voltage controlled crystal reference oscillator anda voltage controlled oscillator in a phase lock loop circuit. Thedigital data stream 34 is used to frequency modulate the carrierfrequency resulting in the radio frequency signal 18 which is thentransmitted through the module antenna 20. The generation of the carrierfrequency is controlled by the module microcontroller 26 throughprogramming in the EEPROM 261, making the module transmitter 28frequency agile over a broad frequency spectrum. In the United Statesand Canada a preferred operating band for the carrier frequency is 902to 928 MHz. The EEPROM 261 can be programmed such that the modulemicrocontroller 26 can instruct the module transmitter 28 to generate acarrier frequency in increments between 902 to 928 MHz. as small asabout 5 to 10 KHz. In the US and other countries of the world, thecarrier frequency may be in the 2400 to 2483.5 MHz. band, 5.725 to 5.875GHz. band, or the 24.0 to 24.25 GHz. band, or other authorized band.This allows the system to be usable in non-North American applicationsand provides additional flexibility.

The voltage controlled crystal oscillator (not shown) in the moduletransmitter 28, not only provides the reference frequency for the moduletransmitter 28 but, advantageously also, provides the clock function 38for the module microcontroller 26 and the A/D means 24 assuring that allcomponents of the signal processing module 16 are synchronized. Analternate design can use a plurality of reference frequency sourceswhere this arrangement can provide certain advantages such as size orpower consumption in the implementation.

The module receiver 29 in the signal processing module 16 receives RFsignals from the base station 40. The signals from the base station 40can be used to operate and control the signal processing module 16 byprogramming and reprogramming the module microprocessor 26 and EEPROM261 therein.

The base station 40 has a base antenna 42 through which RF signals 18are received. Base microcontroller 86 controls the operation of the basestation 40 including base receiver 80, base transmitter 82, and basepower supply 88. Base receiver 80 receives the RF signal 18 from baseantenna 42. The base receiver 80 demodulates the RF signal 18 and thebase microcontroller 86 removes any error correction and performs otherhousekeeping tasks. The data is then downloaded through connector 64 tothe external programming means 60 or other personal computer (PC) ordata storage/viewing device for viewing in real time, storage, oranalysis.

Referring now to FIG. 4, there is shown a block diagram of the inputmeans 22 and A/D means 24 of the signal processing module 16, whichprovides for the data acquisition function of the present invention. Thesignal processing module 16 is variably configurable through softwareprogramming initiated by the external programming means 60 to the EEPROM261 of the microcontroller 26. The variable configurability enables thesignal processing module 16 to receive external inputs 12 havingdifferent characteristics and ranges and to provide variable samplingrate, filtering and gain of the external inputs 12 based upon suchcharacteristics and range and/or the specific application. For example,if the present invention is utilized in a biomedical environment, EEGdiagnosis and monitoring for instance, the sampling rate will need to bemuch higher than it would be for an industrial setting measuringthermocouple readings. The ability to reconfigure the system for varyingsignal characteristics arises at three separate levels in the presentinvention. For maximum flexibility, such reconfiguration can be carriedout during a series of measurements by means of the wireless link, whichis understood in this context to be bidirectional. Depending on thecharacteristics of the received signal 18, the base station 40 cancommand the signal processing module 16 to reconfigure the input means22 and/or A/D means 24 to accept an external input 12 of largeramplitude, or a different frequency range, where signal characteristicschange significantly during the course of a series of measurements.Alternatively, for cost, size, and power advantages, this adjustmentcould be carried out prior to a series of measurements, with theconfiguration information stored in memory in the signal processingmodule 16, where this memory is advantageously implemented in anonvolatile form such as EEPROM 261, allowing the configurationinformation to be retained, for instance, across power outages andobviating the need for module receiver 29 and base transmitter 84,saving cost. A third alternative, which provides advantages in certaintechnical parameters, is to arrange the implementation of the signalprocessing module 16 such that minor changes in component values orparameters can reconfigure the same basic hardware to accept widelydivergent external input 12 types. This reconfiguration could take placeat the factory, providing cost and inventory advantages to themanufacturer, or it could be performed by the end user, providingsimilar cost advantages to the user in allowing one piece of equipmentto perform multiple tasks.

A number of configurable components are shown in FIG. 4. Any givencomponent of this arrangement, though, may be omitted, and, in somecases, the order of the components may be changed to gain certainadvantages such as physical size, power consumption, or cost, withoutchanging the basic spirit of the invention. Components in this FIG. 4may be combined, either by having a single component carry out thefunction of two or more of the components shown or by combiningfunctions within a single package such as an integrated circuit orhybrid module. Certain components may also operate with a fixedconfiguration, limiting the flexibility of certain parameters whileretaining the advantages of configurability in other components.

The external input 12 inputs to the input protection network 221, whichprotects the signal processing module 16 against damage caused by faultsor unanticipated conditions encountered at the external inputs 12.Depending on the rigors expected to be encountered in any givenapplication and the tolerance to size and weight, the input protectionnetwork 221 may be omitted, may consist of a simple resistor network, ormay include more elaborate protection such as diodes, zener diodes,transorbs, gas discharge tubes, and other components commonly known tothose of ordinary skill in the art. Typically, the input protectionnetwork 221 is not configurable but its configurability in the presentinvention provides advantages in certain applications. Configurationoptions can include adjustable limits on input voltage and/or current aswell as rates of change of those parameters, and other electricalparameters as well. These configuration changes can be achieved bychanges to component values on a common platform for smallest size, orcan be changed under processor control by means of various switches suchas relays. A signal within normally expected ranges passes essentiallyunchanged to the measurement type means 222.

The measurement type means 222 allows selection of the external input 12configuration. The measurement type means 222 may be used to configurethe input circuitry to accept external inputs 12 which are single-endedvoltage (a voltage with respect to a common reference shared betweenseveral signals), differential voltage (voltage between two definedconductors), differential current (current flowing through a conductor),single-ended current (current flowing to a common reference), frequency,capacitance, inductance, resistance, impedance, conductivity, or anyother electrical parameter. The measurement type means 222 converts theexternal input 12 to a common parameter such as voltage or current,which can be interpreted by the succeeding blocks regardless of theoriginal type of external signal 12 measured. One input channel can bebuilt with several different measurement type means, which can beselectively enabled by means of an analog switch, such as that found inthe AD7714 chip in the present invention. It is understood that theAD7714 chip can provide many of the functions of the A/D means 24 andthe input means 22 thus reducing the overall size of the signalprocessing module 16. In the preferred embodiment, the output of themeasurement type means 222 is a varying voltage carrying the informationwhich was present in the original signal, or in certain cases, a seriesof voltage measurements, which are then conveyed to the prefilter 223.

The prefilter 223 allows rejection of external inputs 12 of largesignals which are outside the frequency band of interest, so that suchsignals do not saturate the low-noise preamplifier 224. The prefilter223 can be advantageously arranged to be a relatively simple filter toprovide cost, size, and power advantages, because it need only rejectout of band signals to the extent necessary to protect the low-noisepreamplifier 224. A typical application might use a simple “R-C” filterto reject offset voltages in an AC-coupled application, or to rejectextremely high frequencies which fall well beyond the frequency band ofinterest, or a combination of the two. Configurability of this sectioncan be limited to simply enabling or bypassing the prefilter 223, or maybe more elaborate in allowing selection of cutoff frequencies. In thepreferred embodiment this prefilter consists of a simple RC filter whichcan be bypassed under firmware control, to minimize noise injection;however, an alternate embodiment could incorporate electricallyadjustable components such as electronic potentiometers or varactors toprovide even more flexibility at the expense of size and noiseinjection. The prefiltered signal is then passed to the low-noisepreamplifier 224.

The low-noise preamplifier 224 is advantageous in certain applicationsto allow application of gain to the external input 12 early in thesignal chain, before significant noise is introduced by the inherentcharacteristics of certain components, such as thermal noise.Configurability of the gain applied at this step provides an advantagein allowing the present invention to accept larger external inputs 12using a low gain (unity gain or lower), or alternatively to accuratelymeasure very small external inputs 12 with minimal noise by using highergain. This gain can be selectively chosen to be either a fixed value orunity gain under processor control by means of the signal selector builtinto the AD7714 used in the preferred embodiment, or can be designed toallow a selection of one of several gains by means of analog switchescombined with a plurality of gain setting resistors. Gain applied atthis stage has the net effect of dividing any downstream noise by thegain factor applied here. This more robust signal output by thepreamplifier 224 is then passed to the AC coupling filter 225.

The AC coupling filter 225 is a highpass filter used to allow the systemto reject the DC offset or steady state value of an external input 12wherein the offset is not of interest, allowing additional gain to beapplied to the changes in the external input 12. For instance,bioelectric signals such as EEG, EMG, or ECG are normally of interestonly for the changes in those signals, and the absolute offset level isnot of interest for diagnostic purposes. The cutoff frequency may beconfigured to allow adjustment of various parameters such as settlingtime, or may be adjusted to zero to effectively bypass the AC couplingfilter 225. In the preferred embodiment, the filter may be bypassed byuse of the signal selector switch in the AD7714; however, the use ofadjustable components such as electronic potentiometers or varactorswould allow more flexibility in choosing the cutoff frequency, at theexpense of size and power consumption. The resulting signal, nowstripped of any interfering DC offset if so configured, is then passedto the antialias filter 226.

The antialias filter 226 is a lowpass filter required to guard againstfalse signals caused by aliasing between external input 12 content andsampling rate of downstream sampling functions such as multiplexing oranalog-to-digital conversion. The Nyquist sampling theorem shows thatany frequency content in the sampled signal which is higher thanone-half the sampling rate of the sampling function will cause aliasing,which results in false signals. In practice the antialias filter 226 ismore commonly set to a smaller fraction of the sampling rate, usuallybetween ¼ and 1/10 the sampling rate. Regardless of the rate or ratioused, the cutoff frequency of the antialias filter 226 must change whenthe sampling rate changes significantly, to retain the most advantageousratio of the sampling rate to the filter passband. The programmablecutoff frequency of the antialias filter 226 is thus required to allowfor variable sampling rates. In the preferred embodiment, the highsampling rate of the delta sigma modulator in the AD7714 permits the useof a simple fixed RC type filter, with the anitalias filtering beginprovided as an inherent digital filter in the AD7714; however, analternate embodiment might use a switched capacitor filter such as theMAX7409 or other filter with a programmable cutoff frequency. Theresulting filtered signal is then conveyed to the programmable gainamplifier 241 in the A/D means 24.

The programmable gain amplifier 241 adjusts the external input 12amplitude to match the amplitude accepted by the A/D converter 242. Inthe preferred embodiment this programmable gain amplifier is included inthe AD7714 integrated circuit, but this function could also be providedwith a dedicated programmable gain amplifier, or alternatively throughthe use of analog switches or adjustable components such aspotentiometers or DACs. If too much gain is applied, the programmablegain amplifier 241 itself or downstream components will saturate,introducing severe distortion and usually rendering the external input12 immeasurable. If, on the other hand, insufficient gain is appliedhere, the quantization noise of the analog-to-digital conversion processcomes to dominate the external input 12, causing a severe degradation inthe signal-to-noise ratio. For instance, a typical 16-bit A/D converter242 can distinguish between 2.sup.16 or 65536 distinct levels. With anA/D converter 242 input range of .+−0.3 volts, each level represents 92.mu.V. If insufficient gain is applied to the external input 12 suchthat the total signal swing is only 200 .mu.V, the A/D converter 242will convert at most three distinct levels, rendering fine features ofthe external input 12 totally illegible. The module microcontroller 26therefore adjusts the gain applied in the programmable gain amplifier241 such that the expected external input 12 as processed and filteredby the preceding elements as described above, is amplified to cover asmuch of the A/D converter 242 input range as practical, or some othergain which optimizes signal features of interest. Additionally, in someapplications it is advantageous to have the module microcontroller 26adjust this gain dynamically depending upon the actual measured externalinput 12. For instance, the module microcontroller 26 might increase theprogrammable gain amplifier 241 gain when a measured external input 12is very small, and then decrease the gain to avoid saturation when theexternal input 12 amplitude increases. This automatic gain controlprovides an increase in the total dynamic range achievable by the systemwithout requiring expensive, large, and power-hungry components such asvery high resolution A/D converters 242. The signal resulting fromapplication of the specified gain is then passed to the A/D converter242.

At least two parameters of a typical A/D converter 242 can be readilyadjusted to achieve various goals as the situation dictates. First, thesampling rate may be adjusted to balance the conflicting goals of highfidelity measurements and low digital data rate. Where a signal has nohigh frequency content of interest, the sampling rate may be adjusted toa very low rate to minimize the demands on downstream processes such asdigital filtering or telemetering of the data. On the other hand,sampling an external signal 12 with significant high-frequency contentof interest demands a higher sampling rate. In the preferred embodiment,the sampling rate is programmable via the AD7714; in otherimplementations the sampling rate can be made adjustable by means of anexternally applied sampling clock to an A/D converter. The adjustablesampling rate allows the controller to adapt the A/D converter 242 tobest meet the system demands of the moment.

In a similar fashion, selection of the resolution provided by the A/Dconverter 242 must balance faithful reproduction of the external input12 against total digital data rate. Depending on the particular A/Dconverter 242 used, there may also be a tradeoff of the maximumachievable sampling rate against the selected resolution, whereinselection of a higher resolution lowers the maximum attainable samplingrate. Again the module microcontroller 26 can adjust this parameter tobest meet the system requirements, selecting higher resolution whensmaller changes in the measured signal amplitude must be reported, andlower resolution when the lack of such a requirement allows advantagesin the form of either a higher sampling rate or a lower digital datarate. In the preferred embodiment, the AD7714 can be programmed toeither 16 bit or 24 bit resolution, and the firmware running in themicrocontroller can selectively transmit 8, 12, 16, or 24 bits of theacquired data. The digital filter 243, the module microcontroller 26, orother downstream process can also reject certain portions of the digitaldata stream to provide an effective decrease in resolution where thisdecrease is advantageous, especially when the data must later cross abandwidth-limited link such as a RF, IR or optical link. The A/Dconverter 242 passes the signal, now in the form of a succession ofdigital values, to the digital filter 243 for further processing.

The digital filter 243 extracts external input 12 parameters of interestwhile rejecting other signals, commonly referred to as noise.Implementation of the digital filter 243 could alternatively be in theform of analog filters applied anywhere in the signal chain prior to theA/D converter 242, but implementation as a digital filter 243 providesadvantages as to programmability, calibration, drift, and accuracy. Thedigital filter 243 could be implemented in many forms, depending uponthe demands of the particular application. In the preferred embodiment,the digital filter is inherent in the analog to digital conversionprocess inside the AD7714, but it is understood that the digital filter243 could be implemented as firmware inside the module microcontroller26 itself, or as a digital signal processor, or as a specializedintegrated circuit, or by some other means. Regardless ofimplementation, the programmability of the digital filter 243 allows thesystem to readily adapt to changing measurement requirements, whetherthose changes are brought about by changes in the environment, changesin the external input 12 itself, or changes in the focus of the overallsystem. The resulting output from the digital filter 243 is a stream ofdigital values, ready for further processing such as assembly into thedesired format for transmission by the firmware.

Referring now to FIG. 5 there is shown a block diagram of the firmwareof the present invention. The signal processing module 16 firmwaredefines several modes of operation 100. There are several “test” modeswhich are used during factory calibration of the device. In addition,there are several operation modes which have mode-specificconfiguration. For example, the signal processing module 16 can beprogrammed to operate in a first operational mode in which it transmitscalibration data (used to properly zero the analog inputs) for the firstthree seconds of operation (or for some other predetermined time), andthen switches to a second operational mode which transmits analog signalinformation as collected from the A/D converters 242. The configurationfor each mode of operation is programmed in the non-volatile memoryEEPROM 261.

Once power is first applied to the signal processing module 16, themodule microcontroller 26 performs the basic device initialization,including proper configuration of the I/O ports and internal variables102. Next, the module microcontroller 26 reads the initial deviceconfiguration 104 from the EEPROM 261. This configuration controls theinput means 22 of the signal processing module 16, including the numberof external inputs (also herein referred to as channels), the resolutionof the A/D converter 242, and the sampling rate of each individual inputchannel. This configuration also controls the operation of the moduletransmitter 28 in the signal processing module 16, including the carrierfrequency, modulation type, output power control, and the length inbytes of each transmitted RF message packet. This configuration alsodescribes the initial mode of operation for the signal processing module16.

Once the initial configuration has been read, the module microcontroller26 enters the first mode of operation described in the configuration. Itreads the mode-specific configuration 106, which includes the state ofthe module transmitter 28 and the analog inputs as used in the mode.This configuration can reside in EEPROM 261 or in module microcontroller26 memory. The module microcontroller 26 then initializes all theperipheral devices according to this mode configuration 108. In thespecial case that this is the “shutdown” mode, the modulemicrocontroller 26 will perform a software power-down 110.

Once the mode has been initialized, the module microcontroller 26 beginsexecution of the interrupt service routine (ISR) 112, which isresponsible for transmitting the data in the form of messages along themodulated RF carrier. Operation of the interrupt service routine isasynchronous and distinct from the mainline code, and is describedlater.

The module microcontroller 26 begins execution of the mode-specific“opcodes” 114, which are a sequence of instructions contained either inEEPROM 261 or in the module microcontroller 26 memory. These opcodes areperformed for each operational mode. The module microcontroller 26 readsthe first operational code from the EEPROM 261 and interprets theopcode, performing an appropriate action: If the opcode instructs themodule microcontroller 26 to change modes 116, the modulemicrocontroller 26 terminates the ISR 118 and returns to the modeinitialization, and begins execution of a new operational mode; if theopcode instructs the module microcontroller 26 to begin a loop construct120, the module microcontroller 26 begins the loop by initializing aloop counter variable 122; if the opcode instructs the modulemicrocontroller 26 to end a loop construct, the module microcontroller26 increments the loop counter variable and determines if the loop iscomplete 124. If not, the module microcontroller 26 resets the index ofcurrent opcode to the beginning of the loop, otherwise it sets the indexof the next opcode to after the loop; if the opcode instructs the modulemicrocontroller 26 to initialize a single A/D converter 242, the modulemicrocontroller 26 will perform the specified calibration 126; if theopcode instructs the module microcontroller 26 to the read a single A/Dconverter 242, the module microcontroller 26 will take the reading andinsert the data into the current message to be transmitted over the RFcarrier 128; if the opcode instructs the module microcontroller 26 toinsert a special byte of data into the RF message, the modulemicrocontroller 26 will insert this data into the message 130. Thisspecial message byte may include an identifier to uniquely identify thesignal processing module 16, an error check field such as a cyclicredundancy check, or some data representing the internal state of thesignal processing module 16 such as the RF frequency, measuredtemperature, etc.

After each opcode has been read and interpreted, the modulemicrocontroller 26 determines if the RF message has been completelyfilled and is ready to be transmitted over the RF carrier 132. If ithas, the module microcontroller 26 marks a flag variable for theinterrupt service routine to begin transmitting the RF message 134.

Next, the module microcontroller 26 performs any housekeeping tasks,such as updating the RF tuning parameters based on changes intemperature, updating timers, etc. 136. Finally, the modulemicrocontroller 26 returns to execute the next opcode in the sequence114.

Referring now to FIG. 6 there is shown a block diagram of the softwareprogramming function of the ISR 150. The ISR is responsible fortransmitting the individual message bytes over the RF carrier. The ISRis executed by a hardware interrupt which occurs immediately beforeevery byte to be transmitted over the RF carrier. The ISR detectswhether an RF message is completely filled 152. If the ISR detects(based on the flag variable) that an RF message is not yet completelyfilled by the main code, the ISR transmits a “filler” byte, or a bytewith an even number of “1” and “0” bits 154. This acts to maintain aneven (50%) modulation duty cycle on the carrier frequency.

Once the ISR detects that the main code has filled an RF message to betransmitted, it transmits the RF sync bytes 156. These are two uniquebytes transmitted at the beginning of every RF message which are easilyidentified by the base station 40 as the start of a message.

Once the RF sync bytes have been transmitted, the ISR transmits eachmessage byte of the RF message, in sequence 158. Once the RF message hasbeen completely transmitted 160, the ISR resumes transmitting fillerbytes until the next RF message is filled by the main code.

Because of the phase locked loop based frequency synthesizer used in thepresent invention, the module transmitter 28 and base transmitter 84 arefrequency agile over the frequency range. Since the module receiver 29and the base receiver 80 employ automatic frequency control, the presentinvention consumes relatively low power as the module transmitter 28 andbase transmitter 84 can be intermittently powered down without loosingreception due to drift or sacrificing data transmission accuracy. Theutilization of programmable firmware allows inexpensive and flexibleoperation for the inputting, conditioning and processing of any type,character and range of the external inputs. This also allows the modulemicrocontroller 26, in response to the variation of the external inputs12 or, in response to instructions received by RF signal through themodule receiver 29, to adapt the signal processing module 16 based uponthe variations allowing the signal processing means 16 to input,condition, process and transmit said external input notwithstanding saidvariation. The present invention performs this adaptation without theneed to modify or alter hardware or select or use different hardwarealready present in the device. In other words all adaptation can beaccomplished by software programming totally.

One or more sensors are used to develop the data or signals used in thepresent invention for determining a quantitative level of severity of asubject's sleeping disorder and/or symptoms. In various embodiments,preferably at least two EEG electrodes are used to develop this data. Inother embodiments, preferably, at least two ECG electrodes are used. Instill other embodiments, preferably a pulse oximeter is used. In stilleven other embodiments, preferably, either an O₂ or CO₂ blood gasmonitor is used.

The signals from the one or more sensors used in various embodiments ofthe present invention are preferably analyzed using a processor andsoftware that can quantitatively estimate or determine the severity ofthe subject's sleeping disorder or symptoms. Using either themicrocontroller 26 of a data acquisition system, a separate computer,base station or processor, a PDA, a processor on a device for treatingthe subject's sleeping disorder or a combination of these processors,the severity of the subject's sleeping disorder and/or symptoms isdetermined and is used at least in part to regulate the physical orchemical treatment of the subject. Also optionally, the one or moresensors used in the system of the present invention can also be tetheredto a computer, base station, cell phone, a PDA or some other form ofprocessor or microprocessor.

The processor or microprocessor of various embodiments of the presentinvention can be part of a remote communication station or base station.The remote communication station or base station can also be used onlyto relay a pre- or post-processed signal. Preferably, the remotecommunication station or base station can be any device known to receiveRF transmissions such as those transmitted by the wireless dataacquisition system described herein. The remote communication station orbase station by way of example but not limitation can include acommunications device for relaying the transmission, a communicationsdevice for re-processing the transmission, a communications device forre-processing the transmission then relaying it to another remotecommunication station, a computer with wireless capabilities, a PDA withwireless capabilities, a processor, a processor with displaycapabilities, and combinations of these devices. Optionally, the remotecommunication station can further transmit data both to another deviceincluding the subject's treatment device. Further optionally, twodifferent remote communication stations can be used, one for receivingtransmitted data and another for sending data. For example, with thesleep diagnosis and treatment system of the present invention, theremote communication system of the present invention can be a wirelessrouter, which establishes a broadband internet connection and transmitsthe physiological signal to a remote internet site for analysis,preferably for further input by the subject's physician or anotherclinician. Another example is where the remote communication system is aPDA, computer or cell phone, which receives the physiological datatransmission, optionally re-processes the information, and re-transmitsthe information via cell towers, land phone lines, satellite, radiofrequencies or cable to a remote site for analysis. Another example iswhere the remote communication system is a computer or processor, whichreceives the data transmission and displays the data or records it onsome recording medium, which can be displayed or transferred foranalysis at a later time.

The quantitative method for estimating or determining the severity ofthe subject's sleeping disorder or symptoms is preferably accomplishedby using signals or data from the one or more sensors described herein.More preferably, this quantitative method is accomplished in real-time,allowing the subject's symptoms to be treated as they occur. Byreal-time it is meant that the quantitative diagnosis step isaccomplished predictively or within a short period of time aftersymptoms occur which allows for immediate treatment, thereby moreeffectively reducing the health affects of such disorder while at thesame time also minimizing side effects of the treatment chosen. Byreal-time, preferably the diagnosis is accomplished within 24 hours ofreceiving the signals from the one or more sensors on the subject, morepreferably within 8 hours, even more preferably within 4 hours, stilleven more preferably within 1 hour, still even more preferably within 20minutes, still even more preferably within 5 minutes, still even morepreferably within 1 minute, still even more preferably within 10seconds, still even more preferably within 1 second, still even morepreferably within 0.1 seconds and most preferably within 0.01 seconds.

FIG. 7 shows a flow diagram of one example titration algorithm thatadjusts the pressure of a CPAP device based on at least the measuredairflow, respiratory effort, and blood oxygen concentration. Thealgorithm in FIG. 7 consists of a counting phase and an adjustmentphase. The adjustment phase operates in titration mode, during whichlarge pressure adjustments are made, and tuning mode, during which finepressure adjustments are made to establish the optimum air pressure.

First, a time interval and all event counters are reset 202. The systemthen establishes a baseline 206, which is used for comparisonsthroughout the time interval. If the time interval has elapsed 210, thesystem evaluates the event counters and makes adjustments as necessary.The time interval 210 in FIG. 7 is shown as 15 minutes, but any timeperiod may be suitable. For example, early in the titration phase,smaller intervals of 5 minutes may be more appropriate, while later inthe titration phase intervals of 30 minutes or more may be used.

If the time interval has not elapsed 210, the subject's airflow iscompared to the baseline 214. If the subject's current airflow dropsbelow 70% of the baseline for 10 seconds or more 214, the systemevaluates the effects of a severe reduction in airflow. If the airflowdrops to below 10% of the baseline 218, the decrease in airflow mayindicate an instance of apnea. In this situation, the subject's oxygensaturation is compared to the baseline 222. If the subject's oxygensaturation has not decreased more than 3% 222, the decrease in airflowis not an event at all, and the system returns to monitoring thesubject's airflow 210. If the subject's oxygen saturation does decreasemore than 3% 222, the system checks for a breathing effort 226. If thesubject is attempting to breathe, the event is considered an obstructivesleep apnea (OSA), and the OSA_(n) count is increased by one 230. Thesystem then returns to monitoring the subject's airflow 210. If,however, the subject is not attempting to breathe, the system continuesto look for breathing effort 226. If the subject does not attempt tobreathe for more than 4 seconds 234 the event is considered a centralsleep apnea (CSA), and the CSA_(n) count is increased by one 238. Thesystem then returns to monitoring the subject's airflow 210. Incontrast, if the subject does attempt to breathe within 4 seconds 234the event is considered a mixed sleep apnea, and the Mixed_(n) count isincreased by one 242. The system then returns to monitoring thesubject's airflow 210.

Returning to the airflow comparison 218, if the subject's airflow isreduced to 70% of the baseline for 10 seconds or more, but the airflowdoes not drop to 10% of the baseline, the system evaluates the effectsof a mild reduction in airflow. If the airflow does not drop to below10% of the baseline 218, the mild decrease in airflow may indicate aninstance of hypopnea. In this situation, the subject's oxygen saturationis compared to the baseline 246. If the subject's oxygen saturation hasnot decreased more than 4% 246, the decrease in airflow is not an eventat all, and the system returns to monitoring the subject's airflow 210.If the subject's oxygen saturation does decrease more than 4% 246, thesystem checks for a breathing effort 250. If the subject is attemptingto breathe, the event is considered an obstructive sleep hypopnea (OSH),and the OSA_(n) count is increased by one 258. The system then returnsto monitoring the subject's airflow 210. If, however, the subject is notattempting to breathe, the event is considered a central sleep hypopnea(CSH), and the CSH_(n) count is increased by one 254. The system thenreturns to monitoring the subject's airflow 210.

The system continues to monitor the subject throughout the time interval210. After the time interval is over, the system evaluates the subject'scondition and calculates the next change in pressure. If the pressureshould be adjusted 260, an adjustment algorithm is applied. In FIG. 7,the system looks for any event 260, but in other embodiments of thepresent invention the system could evaluate only a few variables, forexample the number of CSA events. Optionally, the system could evaluatethe ratio of counted events, changes in the number of events betweentimeperiods, or any other condition capable of being recorded orcalculated by the system. In FIG. 7, If no events have been detected(i.e., all event counters OSA_(n), CSA_(n), OSH_(n), CSH_(n), andMixed_(n) are 0) 260, the subject's condition is acceptable, and notreatment changes are required. The system then returns and resets thetime interval and all event counters OSA_(n), CSA_(n), OSH_(n), CSH_(n)and Mixed_(n) 202. At this point, the system is also capable ofrecording the previous counter values, recording the total number ofevents, and the like. In this way, the system can compare the subject'sstatus between intervals. For example, the subject's status during thefirst time interval can be compared to the status during the current orfinal interval, or the subject's status can be evaluated overconsecutive intervals. Such comparisons can provide information on, forexample, trends, and overall effectiveness of the treatment.

If an adjustment is appropriate 260, the system determines if anycentral or central-based events have occurred 262. If the subject hasexperienced a central sleep apnea, central sleep hypopnea, or mixedapnea event, the system sets the current pressure as a maximumthreshold, and sets a flag to initiate the tuning phase of the titration266. The new maximum pressure P_(max) is the highest value of pressurethat the system can now attain. Under no circumstances will the systemautomatically increase the air pressure beyond P_(max), although in someembodiments the pressure could be manually adjusted above the maximumvalue. After setting the maximum pressure and initiating the tuningmode, the system decreases the CPAP pressure by 2 cm H₂O 270. The systemthen returns and resets the time interval and all event countersOSA_(n), CSA_(n), OSH_(n), CSH_(n) and Mixed_(n) 202.

If no central or central-based events have occurred, the system checksto see if it is in tuning mode 274. If the system is in tuning mode, andthe subject has experienced an obstructive event (but not a central orcentral-based event) 274, the system compares the result of the nextpressure change to the maximum pressure 290 (established previously at266). If the next pressure increase of 1 cm H₂O will be less than themaximum allowable pressure P_(max) 266, the system increases thepressure by 1 cm H₂O. After making the adjustment, the system thenreturns to the counting phase and resets the time interval and all eventcounters OSA_(n), CSA_(n), OSH_(n), CSH_(n) and Mixed_(n) 202. Incontrast, if the next pressure increase will be greater than or equal tothe maximum allowable pressure P_(max) 266, the titration is complete.The system no longer adjusts the gas pressure, although it may continueto count the subject's events and record other data through theremainder of the night.

If the system is not in tuning mode 274, the system evaluates if theobstructive events were apneas or hypopneas 278. If the events wereapneas, the system increases the gas pressure by 2 cm H₂O 282. If theevents were hypopneas, the system increases the gas pressure by only 1cm H₂O 286. In either case, after adjusting the pressure accordingly,the system then returns and resets the time interval and all eventcounters OSA_(n), CSA_(n), OSH_(n), CSH_(n) and Mixed_(n) 202.

The adjustment algorithm shown in FIG. 7 is relatively simple. Moresophisticated calculations and decisions can also be used. For example,the system can evaluate the trends occurring across time periods byconsidering how the numbers of detected events changes, or the systemcan use the ratio of central-type events to obstructive-type events torefine the changes in pressure. The system could also, for example,consider the number and type of adjustments previously made. Such a stepwould prevent system oscillation that can occur near the end oftitration as the system attempts to refine the optimal pressure. Thesystem could use a variety of analysis and calculation techniques,including lookup tables, fast-Fourier transforms, wavelet analysis,neural networks, and the like.

Although FIG. 7 depicts control of a CPAP machine, any appropriatetreatment device may be used. In this situation, the treatment devicecontrol algorithm would be adjusted to consider the capabilities of thetreatment device. For example, if the treatment device is a moreadvanced bi-level PAP machine, the treatment device control algorithmcould adjust the inspiration air pressure only. The action taken canalso vary. For example, the pressure can be increased by differingamounts depending on the phase of titration, or the number of prioradjustments, or the severity of the breathing events. As furtherillustration, if the system determines that the subject has ansleep-related breathing disorder that is untreatable with the currenttreatment device (for example, a CPAP device cannot deliver asufficiently high pressure, or the treatment device is inappropriate forthe subject's condition), the system can shut down or provide a safepressure for the remainder of the night before recommending anothertreatment method.

Although the titration phase of FIG. 7 is triggered only by the end ofthe time interval 210, various other conditions could also requirepressure adjustments. For example, if the system detects a severecentral apnea event, the gas pressure could be immediately reduced.Similarly, if the system detects several severe apneas in a single timeperiod, the titration phase could begin before the end of the timeperiod. Other safety mechanisms can be programmed into the system aswell. For example, the system can be programmed to ignore the sensorsignals if the data becomes corrupted (for example, if the sensorbecomes disconnected).

FIG. 8 shows a schematic view of one embodiment of the sleep disordertreatment system of the present invention. In FIG. 8, a number ofsensors 420, 424, 418, and 426 are connected to a subject 410. Thesubject 410 in this case is a human shown with a respiratory mask 412,which is connected by an air hose or subject circuit 416 to a continuouspositive air pressure device 428. In this embodiment, the signal or datafrom one or more of these sensors is collected by a diagnostic device441, which comprises a radio 436; an antenna 434; and a microprocessor438 for processing the data or signals to determine a level of severityof the subject's sleeping disorder or symptoms. The diagnostic device441 calculates a level of severity for the subject's symptoms andphysiological condition. The diagnostic device 441 then transmits asignal based on this level of severity by either a tether 444 or radiosignal (not shown) to an actuator (not shown) in the CPAP device 428,which controls the flow of air or gas provided to the subject by the airhose or subject circuit 416. The CPAP device 428 optionally connects toan oxygen tank 430, which can be used to increase the concentration ofoxygen in the air being delivered to the subject. Further optionally,the CPAP device 428 connects to a carbon dioxide tank 431, which can beused to increase the concentration of carbon dioxide in the air beingdelivered to the subject. The CPAP device 428 could connect to both theoxygen tank 430 and the carbon dioxide tank 431, only one of the tanks,or neither. In addition, optionally the treatment device 428 has asensor in the air hose 416, which can measure the differential pressure414 and thereby accurately measure air flow provided to the subject.Also optionally, the device can have a nebulizer (not shown) with areservoir and pump to injecting medication into the nebulizer.

FIG. 9 shows a diagram outlining the treatment titration system in moredetail. In FIG. 9, a patient interface box 16 receives signals (notshown) from a respiratory belt 500 and a pulse oximeter 504 placed onthe subject. The sensors 500 and 504 can be any of the sensors describedherein or known in the art. In a simple embodiment of the presentinvention, the patient interface box 16 generates a wireless signal 18encoded with data corresponding to the signals from the respiratory belt500 and a pulse oximeter 504. The patient interface box 16 transmits thewireless signal 18 to base station 40. In FIG. 9, the wireless signal 18is shown as radio frequency (RF). In this case, the patient interfacebox 16 generates a radio frequency signal 18 by frequency modulating afrequency carrier and transmits the radio frequency signal through themodule antenna 20. The base station 40 receives the radio frequencysignal 18 through base antenna 42, demodulates the radio frequencysignal 18, and decodes the data. It is understood that other wirelessmeans can be utilized with the present invention, such as infrared andoptical, for example. RF wireless transmission is preferred. Althoughone module antenna 16 and one base antenna 42 are shown in thisembodiment, it is understood that two or more types of antennas can beused and are included in the present invention. An external programmingmeans 60, shown in FIG. 9 as a personal computer, contains software thatis used to program the patient interface box 16 and the base station 40through data interface cable 62. The data interface cable 62 isconnected to the base station 40 by connector 64. Instead of a datainterface cable 62, the patient interface box 16 and the base station 40can be programmed by radio frequency (or other type) of signalstransmitted between an external programming means 60 and a base station40 and the patient interface box 16 or to another base station 40. RFsignals, therefore, can be both transmitted and received by both patientinterface box 16 and base station 40. In this event the patientinterface box 16 also includes a module receiver 29 (shown in FIG. 2)while the base station 40 also includes a base transmitter 84 (shown inFIG. 3), in effect making both the patient interface box 16 and the basestation 40 into transceivers. In addition, the data interface cable 62also can be used to convey data from the base station 40 to the externalprogramming means 60. If a personal computer is the external programmingmeans 60, it can monitor, analyze, and display the data in addition toits programming functions. The base receiver 80 and module receiver 29(shown in FIG. 3 and FIG. 2, respectively) can be any appropriatereceivers, such as direct or single conversion types. The base receiver80 preferably is a double conversion superheterodyne receiver while themodule receiver 29 preferably is a single conversion receiver.Advantageously, the receiver employed will have automatic frequencycontrol to facilitate accurate and consistent tuning of the radiofrequency signal 18 received thereby.

The external programming means 60 also contains a processor used tocalculate the next appropriate gas flow level to be delivered to thesubject. In the illustrated embodiment, the external programming means60 uses data originally collected from the respiratory belt 500 and thepulse oximeter 504 to calculate the appropriate flow level. The externalprogramming means 60 is capable of performing a variety of analysis andcalculation techniques, including lookup tables, fast-Fouriertransforms, wavelet analysis, use of a neural network, and the like.Optionally, the data processing and calculation can be performed by thebase station 40. Further optionally, the processing and calculation canbe distributed between the patient interface box 16, the base station40, and the external programming means 60.

After the appropriate flow level has been calculated, the externalprogramming means 60 transmits a command signal to the treatment deviceinterface 518, which then relays the command signal to the treatmentdevice 522 via a connection 518. In FIG. 9, the external programmingmeans 60 transmits the command signal to the treatment device interface518 via wireless RF signal 512. The RF signal 512 is received by an RFantenna 514 on the treatment device interface 518. Optionally, thecommand signal can be transmitted by any other wireless means. Althoughthe command signal transmission 512 is shown in FIG. 9 to be of the sametype as the sensor signal transmission 18, this is not necessary.Optionally, the two wireless transmissions can be of different types.Optionally, the command signal can be transmitted from the externalprogramming means 60 by a wired connection to the treatment deviceinterface 518.

The treatment device interface 518 connects to the treatment device 522with a connector 518. In FIG. 9, the treatment device 522 is shown as aCPAP device, but the treatment device 522 may be any device known in theart for the treatment of sleep-related breathing disorders, includingbut not limited to a bi-level PAP device, an auto-PAP or auto-CPAPdevice, an ASV device, and the like. FIG. 9 also shows the connector 518as a USB connection. Optionally, the treatment device interface 518 canbe completely enclosed within the treatment device 522 itself. In thiscase, the treatment device would be essentially modified to directlyreceive the command signal from the external programming means 60. Oncethe treatment device 522 receives the command signal the treatmentdevice performs the command and changes the treatment provided to thesubject. In FIG. 9, the treatment device 522 is a CPAP device, whichincreases or decreases the pressure of the gas delivered to the subjectvia conduit 526 and mask 530.

Optionally, the treatment device 522 may contain additional sensors. Forexample, if the treatment device 522 is a CPAP device, it may contain anair flow or air pressure sensor (not shown). If the treatment device 522contains a sensor, that sensor information would be integrated into thecommand calculation process. This integration can take place in any ofthe system components. For example, the treatment device sensorinformation could be included in a processing step performed within thetreatment device 522, at the external programming means 60, or at thebase station 40.

FIG. 10 is schematic of the remote data acquisition device and system ofthe present invention. In FIG. 10, a wireless data acquisition system 50is used to receive, filter, and optionally analyze signals 27 fromsensors (not shown) on a subject (not shown). The wireless dataacquisition system 50 transmits a signal based, at least in part, on oneor more of the signals from the sensors on the subject. The dataacquisition system 50 transmits a signal 55 preferably in real time fromthe subject's home 52 to a server 70 for analysis. The signal 55 istransmitted over the internet or other communication system 58. Suchother communication systems include satellites, cellular networks, localarea networks (LAN), other wide area networks (WAN), or othertelecommunications system. If the signal 55 is transmitted over theinternet 58, preferably the signal 55 is transmitted using a cellularcard provided by cellular providers such as for example Sprint,Cingular, AT&T, T-Mobile, Alltel, Verizon or the like. The signal 55that is transmitted over the internet or other communication system 58can be compressed to provide better resolution or greater efficiency.The server 70 performs data analysis (not shown). The analyzed data 73is then entered into a database 76. The analyzed data 73 in the database76 is then accessible and can be requested 79 and sent to multiplereview stations 82 anywhere in the world via the internet or othercommunications system 58 for further analysis and review by clinicians,technicians, researchers, doctors and the like. Signal 84 is a commandsignal for adjusting a parameter of the treatment device. For examplethe signal 84 could instruct the PAP device to increase the pressuredelivered to the subject. The communications systems used for datatransmission need not be the same at all stages. For example, the acellular network can be used to transmit data between the subject's home52 and the remote analysis server 70. Then the internet can be used totransmit data between the remote analysis server 70 and the database 76.Finally in this example, a LAN can be used to transmit data between thedatabase 76 and a review station 82.

FIG. 9 shows a diagram outlining the wireless data acquisition system inmore detail. In FIG. 9, a patient interface box 85 receives signal (notshown) from a sensor 91. This sensor 91 can be an EEG electrode (asshown) or any of the other sensors described herein or known in the art.Although one type of sensor 91 is shown, the patient interface box 85 iscapable of accepting multiple signals from multiple sensors 91. In avery simple embodiment of the present invention, the patient interfacebox 85 generates a wireless signal 94 encoded with data corresponding tothe signal from the sensor 91. The patient interface box 85 transmitsthe wireless signal 94 to base station 97. In FIG. 9, the wirelesssignal 94 is shown as radio frequency (RF). In this case, the patientinterface box 85 generates a radio frequency signal 94 by frequencymodulating a frequency carrier and transmits the radio frequency signalthrough module antenna 100. The base station 97 receives the radiofrequency signal 94 through base antenna 103, demodulates the radiofrequency signal 94, and decodes the data. It is understood that otherwireless means can be utilized with the present invention, such asinfrared and optical, for example. RF wireless transmission ispreferred. Although one module antenna 100 and one base antenna 103 areshown in this embodiment, it is understood that two or more types ofantennas can be used and are included in the present invention. Anexternal programming means 106, shown in FIG. 9 as a personal computer,contains software that is used to program the patient interface box 85and the base station 97 through data interface cable 109. The datainterface cable 109 is connected to the base station 97 by connector112. Instead of a data interface cable 109, the patient interface box 85and the base station 97 can be programmed by radio frequency (or othertype) of signals transmitted between an external programming means 106and a base station 97 and the patient interface box 85 or to anotherbase station 97. RF signals, therefore, can be both transmitted andreceived by both patient interface box 85 and base station 97. In thisevent the patient interface box 85 also includes a module receiver 133(shown on FIG. 2) while the base station 97 also includes a basetransmitter 84, in effect making both the patient interface box 85 andthe base station 97 into transceivers. In addition, the data interfacecable 109 also can be used to convey data from the base station 97 tothe external programming means 106. If a personal computer is theexternal programming means 106, it can monitor, analyze, and display thedata in addition to its programming functions. The base receiver 80 andmodule receiver 133 (shown on FIG. 5) can be any appropriate receivers,such as direct or single conversion types. The base receiver 80preferably is a double conversion superheterodyne receiver while themodule receiver 133 (shown on FIG. 5) preferably is a single conversionreceiver. Advantageously, the receiver employed will have automaticfrequency control to facilitate accurate and consistent tuning of theradio frequency signal 94 received thereby.

FIG. 11 is a diagram of an artifact rejection module 750 that can beused in either the data acquisition system (not shown) or a computer orprocessor (not shown) linked to the data acquisition unit of the presentinvention. In FIG. 11, a subject's EEG signal 752 is preferablycontinuously fed 754 into artifact rejection algorithms within the dataacquisition unit processor. Simultaneously sensor signals 760 from thesubject's movement or motion are also fed into the artifact rejectionprocessor so the EEG signal can be corrected 762 for effects of abnormalor prejudicial motion by the subject. The sensors for determining thesubject's motion are described above, but the most preferred is anaccelerometer that is incorporated into the EEG data acquisition unititself.

A method for the detection and treatment of disordered breathing duringsleep employing wavelet analysis is provided in which data related torespiratory patterns are analyzed with wavelet analysis. Thus allowingfor automatic continuous titration and adjustment of PAP and othertreatment module therapy.

More specifically, this method according to one embodiment of thepresent invention comprises the following steps: placing a mask with atube over a subject's airway, the mask being in communication with asource of a pressurized breathing gas controlled by a PAP, therebyestablishing a respiratory circuit; periodically sampling the gas flowin the circuit; periodically sampling one or several other parametersrelated to the subjects physiological state; periodically calculatingvalues for one or several parameters distinctive of a physiologicalpattern; periodically feeding the parameter values to a processing unitprogrammed to recognize physiological patterns characteristic of sleepdisorders; analyzing the parameter values with wavelet analysis;controlling pressurized breathing gas supply and other treatment modulesor devices in response to the output from the processing unit utilizingwavelet analysis.

Each sensor and/or transducer may generate an analog signalrepresentative of variables being monitored. The monitoring means mayinclude means for amplifying and/or performing analog processing on theanalog signal. The latter may perform filtering and/or other waveshaping functions. The processed signal may be fed to an analog todigital converter to convert each analog signal to a correspondingdigital signal. Each digital signal may be fed to a digital processorsuch as a microprocessor or microcomputer. The digital processorincludes software for deriving subject's respiratory state. The softwaremay include means such as an algorithm for determining from the data agas pressure value which substantially prevents a deterioration of therespiratory state. Preferably the algorithm utilizes wavelet analysis todetect and correct the respiratory event by changing one or severaltreatment parameters. The result may be used to control delivery of gasto the subject to cancel out or substantially compensate the effects ofa sleeping or breathing disorder. In the event that the disorder is notsubstantially corrected the software may be adapted to activate deliveryof a drug such as albuterol, or ipratropium bromide, or the like. Thismay circumvent what may otherwise be a fatal or severe asthma attack.Other drugs or substances may be used depending on the subject's specialneeds. Such as oxygen (O2) or carbon dioxide (CO2) gas could bedelivered to the subject. As mentioned earlier these gases can be usedto aid in respiration. As oxygen can mitigate or relieve the effects ofmany apneas, while a dose of carbon dioxide gas can be used to triggerrespiratory effort in central and complex apneas. The software mayadditionally be adapted to determine quantity requirements of the drug,gas or other therapeutic agent. The latter may be based on the subject'shistory and the extent to which the disorder fails to respond totraditional gas pressure treatment. These drugs and therapeutic agentscould be delivered by any means known in the art, but could includenebulizers, pressurized gas delivering, intravenous auto injection, orsimply allowing the air to flow over a piece of dry ice to sublimatecarbon dioxide into the subject's breathing air.

For a better understanding of the detailed description of the invention,it is necessary to present an overview of the wavelet analysis of thepresent invention.

The wavelet analysis of the present invention, preferably represents asignal as a weighted sum of shifted and scaled versions of the originalmother wavelet, without any loss of information. A single waveletcoefficient is obtained by computing the correlation between the scaledand time shifted version of the mother wavelet and the analyzed part ofa signal. For efficient analysis, scales and shifts take discrete valuesbased on powers of two (i.e., the dyadic decomposition). Forimplementation, filter bank and quadrature mirror filters are utilizedfor a hierarchical signal decomposition, in which a given signal isdecomposed by a series of low- and high-pass filters followed bydownsampling at each stage, see FIG. 3. This analysis is referred to asDiscrete Wavelet Transform (DWT). The particular structure of thefilters is determined by the particular wavelet family used for dataanalysis and by the conditions imposed for a perfect reconstruction ofthe original signal.

The approximation is the output of the low-pass filter, while the detailis the output of the high-pass filter. In a dyadic multiresolutionanalysis, the decomposition process is iterated such that theapproximations are successively decomposed. The original signal can bereconstructed from its details and approximation at each stage (e.g.,for a 3-level signal decomposition, a signal S can be written asS=A3+D3+D2+D1), see FIG. 13. The decomposition may proceed until theindividual details consist of a single sample. The nature of the processgenerates a set of vectors (for instance a.sub.3, d.sub.3, d.sub.2, andd.sub.1 in the three level signal decomposition), containing thecorresponding coefficients. These vectors are of different lengths,based on powers of two, see FIG. 14. These coefficients are theprojections of the signal onto the mother wavelet at a given scale. Theycontain signal information at different frequency bands (e.g., a.sub.3,d.sub.3, d.sub.2, and d.sub.1) determined by the filter bank frequencyresponse. DWT leads to an octave band signal decomposition that dividesthe frequency space into the bands of unequal widths based on powers oftwo, see FIG. 15.

The Stationary Wavelet Transform (SWT) is obtained in a similar fashion,however, the downsampling step is not performed. This leads to aredundant signal decomposition with better potential for statisticalanalysis. The frequency space division is the same as for DWT, see FIG.6.

Despite its high efficiency for signal analysis, DWT and SWTdecompositions do not provide sufficient flexibility for a narrowfrequency bandwidth data analysis (FIG. 13). Wavelet packets, as ageneralization of standard DWT, alleviate this problem. At each stage,details as well as approximations are further decomposed into low andhigh frequency signal components. FIG. 13 shows the wavelet packetdecomposition tree. Accordingly, a given signal can be written in a moreflexible way than provided by the DWT or SWT decomposition (e.g., atlevel 3 we have S=A1+AD2+ADD3+DDD3, where DDD3 is the signal componentof the narrow high frequency band ddd.sub.3). Wavelet packet analysisresults in signal decomposition with equal frequency bandwidths at eachlevel of decomposition. This also leads to an equal number of theapproximation and details coefficients, a desirable feature for dataanalysis and information extraction. FIG. 15 illustrates frequency bandsfor the 3-level wavelet packet decomposition.

Specifically in our application wavelets were adopted due to theirsuitablity for the analysis of non-stationary or transitory features,which characterize most signals found in biomedical applications.Wavelet analysis uses wavelets as basis functions for signaldecomposition.

In the present invention the use of wavelet transform significantlyreduces the computational complexity when performing the task ofassessing the subjects' physiological state based on the acquired signalor signals. Neither a large number of reference signals nor an extensiveamount of clinical data is needed to produce the index disclosedherewith.

This invention involves an observed data set acquired in real-time froma subject. This data set is further compared, in real time, with one ormore reference data sets which characterize distinct physiologicalstates. The comparison yields an index that is later referred to WAVeletindex (abbreviated WAV). The WAVelet index can then be used to assist indistinguishing among the various physiological states, in distinguishingincreasing and decreasing rates of respiration, and in distinguishingincreasing and decreasing level of both obstructive and central airwayapneas, and in distinguishing increasing and decreasing respiratory flowrates and the like.

The observed and reference data sets are statistical representations ofthe wavelet coefficients obtained by applying a wavelet transform ontocorresponding observed and reference signals. These coefficients may beobtained through a wavelet transform of the signal such as standarddyadic discrete wavelet transform (DWT), discrete stationary wavelettransform (SWT), or wavelet packet transform. In this respect, filtersyielding coefficients in a frequency band, chosen such that theirstatistical representation differentiates between respiratory states,can be used for this type of analysis. The choice of this transformationdetermines the computational complexity of the method and the resolutionof the final index. The observed and reference data sets are obtained bycalculating a statistical representation of the transformationcoefficients.

The reference data sets represent distinct physiological states takenfrom the continuum from normal (i.e. no irregularities) to full apnea(i.e. complete lack of ventilation). They can be extracted off-line froma group of subjects or subjects. They are then stored for real-timeimplementation. The transformation selected maximizes the dissimilaritybetween each of the reference data sets.

The comparison between the observed data set against the reference datasets can be based on the computation of the correlation between thesefunctions. However, a computationally less demanding solution is toquantify the similarity between these functions by computing the L1(Manhattan), L2 (Euclidean), or any distance metrics. In the preferredembodiment, where two reference data sets are used, the result of thiscomparison yields two values, each expressing the likelihood of thesubject's physiological states are normal or irregular and to whatdegree. These two values are further combined into a single valuecorresponding to a univariate index of normal/irregular physiologicalstates state, the WAVelet index. This value corresponds to the type andlevel of the condition, which is used to create a proper control signalto the gas flow generator, or turbine, or to other treatment modules.

Most any variant of PAP or CPAP therapy, such as bi-level CPAP therapyor therapy in which the mask pressure is modulated within a breath, canalso be monitored and/or controlled using the methods described herein.Less complex variants of PAP or CPAP therapy could be used, but thebenefits would be much less apparent.

The following figures give a more detailed description of examplecontrol algorithms of the present invention. This example dealsspecifically with control of respiratory gas flow using high noisephysiological signals, although other treatment parameters can bemodified using the same method with proper modification. Also, therespiratory gas flow control and the other treatment methods can be usedconcurrently to correct the subject's physiological state. Some parts ofthis example embodiment may not be needed in some applications dependingon the level of noise associated with a particular physiological signal.FIG. 16 gives an overview of the wavelet analysis functions of thepresent invention in its preferred embodiment. The invention is based onthe wavelet decomposition of the sensor signals in the wavelet analyzerunit 862. This unit 862 applies the wavelet transform onto the finitesignal delivered by the preprocessing unit 860, and then extracts theobserved data set 872 correlated to the respiratory state from thecorresponding wavelet coefficients. This feature function is furtherdelivered to the comparator unit 864, where it is compared with tworeference data sets 874, 876 corresponding to the respiratory state.These reference data sets are calculated off-line and stored in 66 forthe real time comparison in the comparator 864. The result of comparisonis further integrated into an index of respiration, which is the inputof the scaling 868 and filtering 870 units.

Parts of the processing unit 878 contained in the controller 38 thatinvolve signal analysis are detailed in the following.

Pre-Processing Unit

The basic function of the pre-processing unit 80 is to further“clean-up” the signal being analyzed and to reject finite signals thatcontain artifacts or are corrupted. The exact operation of thepreprocessing unit will heavily depend on the type of sensor andphysiological parameter being monitored. The following description issupplied to give a simple overview of the basic function of thepreprocessing unit and a possible method of implementation.

Once a finite signal has been acquired, it is sent to the pre-processingunit, see FIG. 12. It's first stored as a vector x 882 of length N. Themean value 6 x_=k=1 N×k is removed 884. The root mean square amplitude86 of the finite signal is then calculated as: 7 rms=1 Nk=1 N (xk) 2(9).

Finite signals with amplitudes greater than some maximum value and lessthan some minimum value are then rejected. It is assumed that theyeither contain artifacts or the data is corrupted possibly duedisconnection of a sensor. If the amplitude is within the two bounds892, a flag 894 indicating that the finite signal is not corrupted takesthe value 1. In this case, the finite signal is normalized 896 as: 8 xk=×k rms, k=1 , , , N (10).

The amplitude normalization allows better focus on the phase andfrequency content of the finite signal, rather than its amplitude. Soamplitude normalization is especially well suited for bio-potentialmeasurements such as EEG, EMG, or ECG.

If an artifact is present 888, the flag is put to 0 and the algorithmproceeds to the scaling unit 811. If normal breathing is detected 890,the flag takes the value 1 and the variable WAV_unfilt 898 takes thevalue of 0. The apparatus then proceeds to send the signal to thefiltering unit 870. The apparatus then proceeds to the next stage, (i.e.the wavelet analyzer unit denoted by 862 in FIG. 12 and FIG. 16).

Wavelet Analyzer Unit

The wavelet analyzer unit 862 first calculates the wavelet coefficientsapplying the SWT and the wavelet filter to the pre-processed finitesignal. The coefficients are obtained by convolution of the signal withthe wavelet filter.

The coefficients corresponding to the band selected in the off-lineanalysis as the most discriminating (in this embodiment: d, are thenstored in a vector C. The probability density function is then obtainedby calculating the histogram of the coefficients in vector C. The vectorof histogram contains b coefficients, where b is chosen number of bins(e.g. 100). Each element of this vector is then divided by the totalnumber of coefficients in d.sub.1 band, i.e. by the length of a vectorC. The result is a vector pdf of length b, which represents theprobability density function of wavelet coefficients in d.sub.1 bandobtained by the wavelet decomposition of the finite signal x.

Comparator Unit

The resulting pdf vector is input into comparator unit 864, see FIG. 17.This unit compares the pdf vector of a current signal 872 with tworeference vectors pdf.sub.w and pdf.sub.a representing two knownrespiratory states non-apneic 874 and apneic 876.

The non-apneic reference data set 74 is derived from a combination ofsignals obtained from a group of healthy subjects (population norming).This reference data set can be then stored on a mass storage device forfuture real time comparison. Another possibility is to record thesubject's respiratory signals while the subject is in a non-apneicstate, and then derive the reference data set (self-norming).

The apneic reference data set 876 is the PDF of the wavelet coefficientsof an apneic signal, which is either derived or recorded from an actualsubject which mimics the most severe level of apneas.

The comparison 900 between the pdf 872 calculated in the waveletanalyzer unit 862 and the two reference data sets pdf.sub.w 874 and pdf.sub.a 876 is achieved using the L1 distance metric. This comparisonyields two values i.sub.w 902 and i.sub.a 906.

An index i 908 is then generated by calculating 904 the differencebetween i.sub.w 902 and i.sub.a 906:i=i.sub.a-i.sub.w  (12)The output of the comparator unit is then input to the scaling unit 868.Scaling Unit

The index i 908 is scaled in order to take values between 0%(corresponding to an apneic signal) and 100% (corresponding to thenon-apneic baseline) with higher values indicating higher level ofrespiratory function:i=i.multidot.scale+offset  (13)scale and offset are two fixed values calculated in the offlineanalysis. The result of the scaling is further stored into the variableWAV_unfilt 898.Filtering Unit

The variable WAV_unfilt 898 contains the unfiltered version of the finalWAVelet index. The random character of the some signals dictates that inorder to extract a more representative trend of the subject'srespiratory state it may be necessary to smooth this variable using afilter.

A new value WAV_unfilt is delivered by the scaling unit 868 for everyfinite signal (i.e. every second or every fraction of a second in thepreferred embodiment). However, note that if the current epoch iscorrupted with an artifact, the variable WAV_unfilt can take anarbitrary value, as it will not be used to derive the final value of theindex.

The result of the averaging filter is stored in the variable WAV.However, when calculating the average, only uncorrupted finite signalsare taken into account by investigating the corresponding flag variable.The WAV variable is finally sent to the controller 838 which thenproduces the appropriate command signal.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the present inventionwithout departing from the spirit and scope of the invention. Thus, itis intended that the present invention cover the modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

What we claim is:
 1. A system for adjusting a positive airway pressuredevice comprising: a PAP device adapted to treat a patient's sleepapnea, a data acquisition system comprising at least one sensor adaptedto generate a first electrical signal, a data acquisition box comprisinga first electronic component or connection adapted to connect the atleast one sensor and receiving the first electrical signal from the atleast one sensor, and a second electronic component or connectionadapted to receive a second electrical signal based on a PAP sensorwithin the PAP device, wherein the PAP device adapted to be separate andin a different enclosure from the data acquisition box, and a processoradapted to identify central apneas and hypopneas from the first andsecond electrical signals, to differentiate the central apneas andhypopneas from obstructive apneas and hypopneas, and to modify treatmentof the PAP device based on the identified central apneas and hypopneas.2. The system of claim 1, wherein the data acquisition system comprisesat least two sensors, each of the at least two sensors adapted togenerate an electrical signal, the at least two sensors including arespiratory effort belt and a pulse oximeter, and the processor isadapted to identify central apneas when the pulse oximeter measurementdrops by at least 3% and the thoracic effort ceases based on theelectrical signals of the at least two sensors.
 3. The system of claim1, wherein the data acquisition system is adapted to train the PAPdevice during titration or adjustment so that the PAP device correlatesmore robust or rich signal data collected with the data acquisitionsystem with a more limited sensor data from the PAP device using aprocessor on the PAP device.
 4. The system of claim 1, wherein theprocessor is further adapted to modify a treatment of an additionaltreatment device configured to treat central or complex apneas.
 5. Thesystem of claim 4, wherein the additional treatment device is selectedfrom the group consisting of an O₂ tank or source, a CO₂ tank or source,a medication or chemical reservoir, a functional electrical stimulationdevice and combinations thereof.
 6. The system of claim 1, wherein thedata acquisition system is adapted to receive the first and secondelectrical signals from at least two sensors, the at least two sensorsincluding a respiratory effort belt and a flow or pressure sensor, andthe first and second electrical signals from the at least two sensorsare received by the processor.
 7. A system for adjusting a positiveairway pressure (PAP) device and treating obstructive, central and mixedapneas and hyponeas comprising: a PAP device adapted to treat apatient's sleep apnea; and a data acquisition system comprising at leastone sensor adapted to generate a first electrical signal, and a dataacquisition box comprising a first electronic component or connectionadapted to connect the at least one sensor and receiving the firstelectrical signal from the at least one sensor, and a second electroniccomponent or connection adapted to receive a second electrical signalbased on a PAP sensor within the PAP device, wherein the PAP deviceadapted to be separate and in a different enclosure from the dataacquisition box; a processor adapted to identify central apneas andhypopneas from the first and second electrical signals, to differentiatethe central apneas and hypopneas from obstructive apneas and hypopneas,and to modify treatment by the PAP device based on the identifiedcentral apneas and hypopneas; and a chemical treatment device comprisingone or more of an O₂ source, a CO₂ source, and/or a medication source,the chemical treatment device adapted to be either integral to orseparate from the PAP device, and the processor being further adapted tomodify a treatment by the chemical treatment device.
 8. The system ofclaim 7, wherein the chemical treatment device is a medication reservoirplaced inline with the airflow of the PAP device and configured todeliver a nebulized medication or drug to the patient's lungs.
 9. Thesystem of claim 7, wherein the data acquisition system is modular andafter a limited period of time is detachable from the PAP device. 10.The system of claim 7, the airflow of the PAP device has a concentrationof carbon dioxide, and wherein the chemical treatment is a CO₂ sourceconfigured to increase the concentration of carbon dioxide in theairflow being delivered to the patient with the PAP device.
 11. Thesystem of claim 7, the airflow of the PAP device has a concentration ofoxygen, and wherein the chemical treatment is an O₂ source configured toincrease the concentration of oxygen in the airflow being delivered tothe patient with the PAP device.
 12. The system of claim 7, wherein theat least one sensor comprises a pulse oximetry sensor and a respiratoryeffort belt, wherein the processor identifies central apneas, in part,when the pulse oximeter measurement drops by 3% and the respiratoryeffort measurement ceases based on the electrical signals of the pulseoximetry sensor and the respiratory effort belt.
 13. The system of claim7, wherein the processor is further adapted to modify a treatment of anadditional treatment device configured to treat central or complexapneas, the additional treatment device being a function electricalstimulation device.
 14. A method of treating a sleep-related breathingdisorder comprising steps of: attaching a first sensor to a subjectsleeping at home or at a facility remote from a sleep analysis lab andreceiving PAP or CPAP therapy; concurrently providing therapy to thesubject with a PAP or CPAP device; connecting, before or after attachingthe first sensor to the subject, the first sensor to a data acquisitionsystem, the data acquisition system comprising a data acquisition box,which is separate from the PAP or CPAP device and adapted to receive afirst electrical signal from the first sensor; collecting data from thefirst sensor attached to the subject during a time period while thesubject attempts to sleep; collecting during the time period andtransmitting a second electrical signal from a second sensor integratedinto the PAP or CPAP device to the data acquisition system, the deviceadapted to deliver a flow of pressurized gas to the subject; andadjusting or titrating the flow of the pressurized gas delivered by thePAP or CPAP device using at least part of the data from both the firstand second sensor signals to identify central apneas and hypopneas anddifferentiate the central apneas and hypopneas from obstructive apneasand hypopneas to improve therapy to the subject utilizing the PAP orCPAP after the time period when data is no longer collected from thefirst sensor.
 15. The method of claim 14, wherein the data acquisitionbox and the PAP or CPAP device each have a wireless RF connection andthe data from the second integrated sensor is transmitted wirelesslydirectly from the PAP or CPAP device to the data acquisition box in realtime.
 16. The method of claim 14, with the further step wherein the datafrom the first and second sensors is at least in part transmitted fromthe data acquisition system by cellular service, land lines or theinternet to a remote data storage station for review remotely by medicalpersonnel, and the medical personnel provides a command signaltransmitted by cellular service, land lines or the internet fortitrating or adjusting the PAP or CPAP device automatically if necessaryto adjust the flow or by communicating with an individual near thesubject or with the subject to adjust the PAP or CPAP device.
 17. Themethod of claim 14, wherein the steps of the method is used to adjust ortitrate the PAP or CPAP device to better identify and distinguishbetween obstructive, central and complex sleep apneas and the PAP orCPAP device is adjusted, titrated or discontinued based on this analysisafter the time period when data is no longer collected from the firstsensor.
 18. The method of claim 14, wherein the data acquisition systemcomprises the first sensor and a third sensor, the first and thirdsensors adapted to generate electrical signals including a respiratoryeffort belt sensor, and a pulse oximetry sensor, and the second sensorintegrated into the PAP or CPAP device is a flow or pressure sensor,wherein the PAP or CPAP device is adjusted or titrated using, in part,data from the first, second and third sensors to improve therapy to thesubject utilizing the PAP or CPAP after the time period when data is nolonger collected from the first and third sensors.
 19. The method ofclaim 14, wherein the PAP or CPAP device is automatically titrated oradjusted based on physiological signals that are specific to the subjectbeing treated for improved treatment after the time period when data isno longer collected from the first sensor.
 20. The method of claim 14,further comprising the step of modifying a treatment of an additionaltreatment device configured to treat central or complex apneas based atleast in part on the data from the first and second electrical signals,wherein the additional treatment device is selected from the groupconsisting of an O₂ tank or source, a CO₂ tank or source, a medicationor chemical reservoir, a functional electrical stimulation device andcombinations thereof.